Latent space simulators

This page was last updated on 2024-07-17 08:46:07 UTC

Manually curated articles on Latent space simulators

Abstract Title Authors Publication Date Journal/ Conference Citation count Highest h-index View recommendations
visibility_off Molecular latent space simulators Hythem Sidky, Wei Chen, Andrew L. Ferguson 2020-07-01 Chemical Science 31 35 open_in_new
visibility_off Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics C. Wehmeyer, F. Noé 2017-10-30 The Journal of chemical physics, Journal of Chemical Physics 334 61 open_in_new
visibility_off VAMPnets for deep learning of molecular kinetics Andreas Mardt, Luca Pasquali, Hao Wu, F. Noé 2017-10-16 Nature Communications 463 61 open_in_new
visibility_off Nonlinear Discovery of Slow Molecular Modes using Hierarchical Dynamics Encoders Wei Chen, Hythem Sidky, Andrew L. Ferguson 2019-02-09 The Journal of chemical physics, Journal of Chemical Physics 77 35 open_in_new
visibility_off Variational Approach for Learning Markov Processes from Time Series Data Hao Wu, Frank No'e 2017-07-14 Journal of Nonlinear Science 211 23 open_in_new
Abstract Title Authors Publication Date Journal/ Conference Citation count Highest h-index View recommendations

Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index
visibility_off From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach Timothée Devergne, Vladimir Kostic, Michele Parrinello, Massimiliano Pontil 2024-06-13 ArXiv 0 1
visibility_off Information Bottleneck Approach for Markov Model Construction. Dedi Wang, Yunrui Qiu, E. Beyerle, Xuhui Huang, P. Tiwary 2024-06-10 Journal of chemical theory and computation 0 30
visibility_off Augmenting Human Expertise in Weighted Ensemble Simulations through Deep Learning based Information Bottleneck Dedi Wang, P. Tiwary 2024-06-21 ArXiv 0 30
visibility_off DeepLNE++ leveraging knowledge distillation for accelerated multi-state path-like collective variables Thorben Frohlking, Valerio Rizzi, Simone Aureli, F. L. Gervasio 2024-07-05 ArXiv 0 4
visibility_off Coarse-graining conformational dynamics with multi-dimensional generalized Langevin equation: how, when, and why Pinchen Xie, Yunrui Qiu, E. Weinan 2024-05-20 ArXiv 0 1
visibility_off Learning data efficient coarse-grained molecular dynamics from forces and noise Aleksander E. P. Durumeric, Yaoyi Chen, Frank No'e, Cecilia Clementi 2024-07-01 ArXiv 0 10
visibility_off Data-Driven Linearization of Dynamical Systems George Haller, B. Kasz'as 2024-07-11 ArXiv 0 0
visibility_off Sparsifying dimensionality reduction of PDE solution data with Bregman learning T. J. Heeringa, Christoph Brune, Mengwu Guo 2024-06-18 ArXiv 0 1
visibility_off Learning the Infinitesimal Generator of Stochastic Diffusion Processes Vladimir Kostic, Karim Lounici, Helene Halconruy, Timothée Devergne, M. Pontil 2024-05-21 ArXiv 1 70
visibility_off Limits and Powers of Koopman Learning Matthew J. Colbrook, Igor Mezi'c, Alexei Stepanenko 2024-07-08 ArXiv 0 16
visibility_off From high-dimensional committors to reactive insights Nils E. Strand, Schuyler B. Nicholson, Hadrien Vroylandt, Todd R. Gingrich 2024-06-03 ArXiv 0 17
visibility_off Implementation of Girsanov Reweighting in OpenMM and Deeptime Joana-Lysiane Schäfer, Bettina G Keller 2024-06-12 The Journal of Physical Chemistry. B 0 0
visibility_off RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators Gianluca Fabiani, Ioannis G. Kevrekidis, Constantinos Siettos, A. Yannacopoulos 2024-06-08 ArXiv 0 17
visibility_off Accurate nuclear quantum statistics on machine-learned classical effective potentials I. Zaporozhets, Felix Musil, V. Kapil, Cecilia Clementi 2024-07-03 ArXiv 0 15
visibility_off VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification Paolo Conti, Jonas Kneifl, Andrea Manzoni, A. Frangi, Jörg Fehr, S. Brunton, J. Kutz 2024-05-31 ArXiv 0 63
visibility_off Kinetics-Optimized Enhanced Sampling Using Mean First Passage Times Tiejun Wei, B. Dudas, E. Rosta 2024-06-13 ArXiv 0 36
visibility_off Recurrent Deep Kernel Learning of Dynamical Systems N. Botteghi, Paolo Motta, Andrea Manzoni, P. Zunino, Mengwu Guo 2024-05-30 ArXiv 0 6
visibility_off Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems Katiana Kontolati, S. Goswami, G. Em Karniadakis, Michael D Shields 2024-06-14 Nature Communications 0 19
visibility_off Coarse Grained Molecular Dynamics with Normalizing Flows Samuel Tamagnone, Alessandro Laio, Marylou Gabri'e 2024-06-03 ArXiv 1 1
visibility_off Weak Generative Sampler to Efficiently Sample Invariant Distribution of Stochastic Differential Equation Zhiqiang Cai, Yu Cao, Yuanfei Huang, Xiang Zhou 2024-05-29 ArXiv 0 1
visibility_off Predicting Future Kinetic States of Physicochemical Systems Using Generative Pre-trained Transformer Palash Bera, Jagannath Mondal 2024-06-19 bioRxiv 0 4
visibility_off Thermodynamically Informed Multimodal Learning of High-Dimensional Free Energy Models in Molecular Coarse Graining Blake R. Duschatko, Xiang Fu, Cameron Owen, Yu Xie, Albert Musaelian, T. Jaakkola, Boris Kozinsky 2024-05-29 ArXiv 2 97
visibility_off Towards latent space evolution of spatiotemporal dynamics of six-dimensional phase space of charged particle beams M. Rautela, Alan Williams, A. Scheinker 2024-06-03 ArXiv 0 20
visibility_off Foundation Inference Models for Markov Jump Processes David Berghaus, K. Cvejoski, Patrick Seifner, C. Ojeda, Ramses J. Sanchez 2024-06-10 ArXiv 0 7
visibility_off Nonlinear denoising score matching for enhanced learning of structured distributions Jeremiah Birrell, M. Katsoulakis, Luc Rey-Bellet, Benjamin J. Zhang, Wei Zhu 2024-05-24 ArXiv 0 31
visibility_off Model Predictive Control of the Neural Manifold Christof Fehrman, C. D. Meliza 2024-06-21 ArXiv 0 6
visibility_off Physics-informed deep learning and compressive collocation for high-dimensional diffusion-reaction equations: practical existence theory and numerics Simone Brugiapaglia, N. Dexter, Samir Karam, Weiqi Wang 2024-06-03 ArXiv 1 9
visibility_off Transferable Boltzmann Generators Leon Klein, Frank No'e 2024-06-20 ArXiv 0 2
visibility_off Learning dynamical systems from data: An introduction to physics-guided deep learning Rose Yu, Rui Wang 2024-06-24 Proceedings of the National Academy of Sciences of the United States of America 1 1
visibility_off On instabilities in neural network-based physics simulators Daniel Floryan 2024-06-18 ArXiv 0 0
visibility_off WgLaSDI: Weak-Form Greedy Latent Space Dynamics Identification Xiaolong He, April Tran, David M. Bortz, Youngsoo Choi 2024-06-29 ArXiv 0 3
visibility_off Identification of Recurrent Dynamics in Distributed Neural Populations R. Osuna-Orozco, Edward Castillo, K. Harris, Samantha R. Santacruz 2024-06-01 bioRxiv 0 15
visibility_off Identifying latent state transition in non-linear dynamical systems cCauglar Hizli, cCaugatay Yildiz, Matthias Bethge, ST John, Pekka Marttinen 2024-06-05 ArXiv 0 2
visibility_off What's the score? Automated Denoising Score Matching for Nonlinear Diffusions Raghav Singhal, Mark Goldstein, Rajesh Ranganath 2024-07-10 ArXiv 0 7
visibility_off Cascade of phase transitions in the training of Energy-based models Dimitrios Bachtis, Giulio Biroli, A. Decelle, Beatriz Seoane 2024-05-23 ArXiv 2 14
visibility_off Stable tensor neural networks for efficient deep learning Elizabeth Newman, L. Horesh, H. Avron, M. Kilmer 2024-05-30 Frontiers in Big Data 1 34
visibility_off An Empirical Investigation on Variational Autoencoder-Based Dynamic Modeling of Deformable Objects from RGB Data Tomás Coleman, R. Babuška, Jens Kober, C. D. Santina 2024-06-11 2024 32nd Mediterranean Conference on Control and Automation (MED) 0 20
visibility_off Sifting through the Noise: A Survey of Diffusion Probabilistic Models and Their Applications to Biomolecules Trevor Norton, Debswapna Bhattacharya 2024-05-31 ArXiv 0 15
visibility_off Nuclear Norm Regularization for Deep Learning Christopher Scarvelis, Justin Solomon 2024-05-23 ArXiv 0 3
visibility_off Neural Data-Enabled Predictive Control Mircea Lazar 2024-06-12 ArXiv 0 1
visibility_off Fast, accurate training and sampling of Restricted Boltzmann Machines Nicolas B'ereux, A. Decelle, Cyril Furtlehner, Lorenzo Rosset, Beatriz Seoane 2024-05-24 ArXiv 0 14
visibility_off Learning to Approximate Particle Smoothing Trajectories via Diffusion Generative Models Ella Tamir, Arno Solin 2024-06-01 ArXiv 0 2
visibility_off Delay Embedding Theory of Neural Sequence Models Mitchell Ostrow, Adam J. Eisen, I. Fiete 2024-06-17 ArXiv 0 30
visibility_off Collective Variable Free Transition Path Sampling with Generative Flow Network Kiyoung Seong, Seonghyun Park, Seonghwan Kim, Woo Youn Kim, Sungsoo Ahn 2024-05-30 ArXiv 0 3
visibility_off Deep Koopman Learning using the Noisy Data Wenjian Hao, Devesh Upadhyay, Shaoshuai Mou 2024-05-26 ArXiv 0 3
visibility_off Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models G. A. Padmanabha, J. Fuhg, C. Safta, Reese E. Jones, N. Bouklas 2024-06-30 ArXiv 0 18
visibility_off Latent Diffusion for Neural Spiking Data J. Kapoor, Auguste Schulz, Julius Vetter, Felix Pei, Richard Gao, J. H. Macke 2024-06-27 ArXiv 0 2
visibility_off Gaussian process regression + deep neural network autoencoder for probabilistic surrogate modeling in nonlinear mechanics of solids Saurabh Deshpande, Hussein Rappel, Mark Hobbs, Stéphane P. A. Bordas, Jakub Lengiewicz 2024-07-15 ArXiv 0 4
visibility_off Iterative Sparse Identification of Nonlinear Dynamics Jinho Choi 2024-06-06 ArXiv 0 0
visibility_off Variational time reversal for free energy estimation in nonequilibrium steady states Jorge L. Rosa-Ra'ices, David T. Limmer 2024-06-03 ArXiv 0 32
visibility_off Inferring stochastic low-rank recurrent neural networks from neural data Matthijs Pals, A. E. Saugtekin, Felix Pei, Manuel Gloeckler, J. H. Macke 2024-06-24 ArXiv 0 3
visibility_off Nonlinear time-series embedding by monotone variational inequality Jonathan Y. Zhou, Yao Xie 2024-06-11 ArXiv 0 0
visibility_off Unambiguous Models and Machine Learning Strategies for Anomalous Extreme Events in Turbulent Dynamical System D. Qi 2024-06-01 Entropy 0 13
visibility_off Refining Potential Energy Surface through Dynamical Properties via Differentiable Molecular Simulation Bin Han, Kuang Yu 2024-06-26 ArXiv 0 0
visibility_off Computing Nonequilibrium Responses with Score-shifted Stochastic Differential Equations J'er'emie Klinger, Grant M. Rotskoff 2024-06-20 ArXiv 0 24
visibility_off Computing the committor with the committor to study the transition state ensemble Peilin Kang, Enrico Trizio, Michele Parrinello 2024-06-05 Nature computational science 0 4
visibility_off Paired Autoencoders for Inverse Problems Matthias Chung, Emma Hart, Julianne Chung, B. Peters, Eldad Haber 2024-05-21 ArXiv 0 13
visibility_off An improved penalty-based excited-state variational Monte Carlo approach with deep-learning ansatzes P. B. Szab'o, Zeno Schatzle, Mike T. Entwistle, Frank No'e 2024-05-27 ArXiv 1 2
visibility_off Dynamical Measure Transport and Neural PDE Solvers for Sampling Jingtong Sun, Julius Berner, Lorenz Richter, Marius Zeinhofer, Johannes Muller, K. Azizzadenesheli, A. Anandkumar 2024-07-10 ArXiv 0 31
visibility_off Dynamical mixture modeling with fast, automatic determination of Markov chains Christopher E Miles, Robert J. Webber 2024-06-07 ArXiv 0 8
visibility_off Latent Functional Maps Marco Fumero, Marco Pegoraro, Valentino Maiorca, Francesco Locatello, Emanuele Rodolà 2024-06-20 ArXiv 0 7
visibility_off How more data can hurt: Instability and regularization in next-generation reservoir computing Yuanzhao Zhang, Sean P. Cornelius 2024-07-11 ArXiv 0 1
visibility_off Thermodynamic Transferability in Coarse-Grained Force Fields using Graph Neural Networks Emily Shinkle, Aleksandra Pachalieva, Riti Bahl, Sakib Matin, Brendan Gifford, G. Craven, Nicholas Lubbers 2024-06-17 ArXiv 0 15
visibility_off Alternators For Sequence Modeling Mohammad Reza Rezaei, Adji B. Dieng 2024-05-20 ArXiv 0 13
visibility_off MPSDynamics.jl: Tensor network simulations for finite-temperature (non-Markovian) open quantum system dynamics Thibaut Lacroix, Brieuc Le D'e, Angela Riva, A. Dunnett, Alex W Chin 2024-06-11 ArXiv 1 5
visibility_off Learning glass transition temperatures via dimensionality reduction with data from computer simulations: Polymers as the pilot case Artem Glova, Mikko Karttunen 2024-06-28 ArXiv 0 0
visibility_off Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation Can Yaras, Peng Wang, Laura Balzano, Qing Qu 2024-06-06 ArXiv 0 4
visibility_off Low-dimensional approximations of the conditional law of Volterra processes: a non-positive curvature approach Reza Arabpour, John Armstrong, Luca Galimberti, Anastasis Kratsios, Giulia Livieri 2024-05-30 ArXiv 0 6
visibility_off Neural Thermodynamic Integration: Free Energies from Energy-based Diffusion Models Bálint Máté, Franccois Fleuret, Tristan Bereau 2024-06-04 ArXiv 0 11
visibility_off Machine Learning Conservation Laws of Dynamical systems Meskerem Abebaw Mebratie, Rudiger Nather, Guido Falk von Rudorff, Werner M. Seiler 2024-05-31 ArXiv 0 5
visibility_off Randomized Physics-Informed Neural Networks for Bayesian Data Assimilation Yifei Zong, D. Barajas-Solano, A. Tartakovsky 2024-07-05 ArXiv 0 41
visibility_off Diffusion Spectral Representation for Reinforcement Learning Dmitry Shribak, Chen-Xiao Gao, Yitong Li, Chenjun Xiao, Bo Dai 2024-06-23 ArXiv 0 0
visibility_off Markovian Gaussian Process: A Universal State-Space Representation for Stationary Temporal Gaussian Process Weihan Li, Yule Wang, Chengrui Li, Anqi Wu 2024-06-29 ArXiv 0 1
visibility_off Accelerated Inference for Partially Observed Markov Processes using Automatic Differentiation Kevin Tan, Giles Hooker, E. Ionides 2024-07-03 ArXiv 0 29
visibility_off An Efficient Approach to Regression Problems with Tensor Neural Networks Yongxin Li 2024-06-14 ArXiv 0 0
visibility_off Minimum Reduced-Order Models via Causal Inference Nan Chen, Honghu Liu 2024-06-29 ArXiv 0 0
visibility_off Stochastic Reservoir Computers Peter J. Ehlers, H. Nurdin, Daniel Soh 2024-05-20 ArXiv 0 22
visibility_off Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation Madison Cooley, Shandian Zhe, R. Kirby, Varun Shankar 2024-06-04 ArXiv 0 19
visibility_off Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing Viktor Zaverkin, Francesco Alesiani, Takashi Maruyama, Federico Errica, Henrik Christiansen, Makoto Takamoto, Nicolas Weber, Mathias Niepert 2024-05-23 ArXiv 1 9
visibility_off Adaptive RKHS Fourier Features for Compositional Gaussian Process Models Xinxing Shi, Thomas Baldwin-McDonald, Mauricio A. 'Alvarez 2024-07-01 ArXiv 0 1
visibility_off Linearization Turns Neural Operators into Function-Valued Gaussian Processes Emilia Magnani, Marvin Pförtner, Tobias Weber, Philipp Hennig 2024-06-07 ArXiv 0 3
visibility_off Symplectic Methods in Deep Learning S. Maslovskaya, S. Ober-Blöbaum 2024-06-06 ArXiv 0 22
visibility_off Fast and Tuning-free Nonlinear Data Embedding and Integration based on DCOL Shengjie Liu, Tianwei Yu 2024-06-09 bioRxiv 0 1
visibility_off High Rank Path Development: an approach of learning the filtration of stochastic processes Jiajie Tao, Hao Ni, Chong Liu 2024-05-23 ArXiv 0 1
visibility_off Stochastic Gradient Descent for Two-layer Neural Networks Dinghao Cao, Zheng-Chu Guo, Lei Shi 2024-07-10 ArXiv 0 0
visibility_off Deep Learning for Computing Convergence Rates of Markov Chains Yanlin Qu, Jose Blanchet, Peter Glynn 2024-05-30 ArXiv 0 3
visibility_off Space-Time Continuous PDE Forecasting using Equivariant Neural Fields David M. Knigge, David R. Wessels, Riccardo Valperga, Samuele Papa, J. Sonke, E. Gavves, E. J. Bekkers 2024-06-10 ArXiv 1 56
visibility_off Kolmogorov Arnold Informed neural network: A physics-informed deep learning framework for solving PDEs based on Kolmogorov Arnold Networks Yizheng Wang, Jia Sun, Jinshuai Bai, C. Anitescu, M. Eshaghi, X. Zhuang, T. Rabczuk, Yinghua Liu 2024-06-16 ArXiv 4 69
visibility_off Tree-like process tensor contraction for automated compression of environments M. Cygorek, B. Lovett, Jonathan Keeling, E. Gauger 2024-05-26 ArXiv 1 30
visibility_off Accurate Conformation Sampling via Protein Structural Diffusion Jiahao Fan, Ziyao Li, Eric Alcaide, Guolin Ke, Huaqing Huang, E. Weinan 2024-05-21 bioRxiv 0 4
visibility_off Exciting DeePMD: Learning excited state energies, forces, and non-adiabatic couplings Lucien Dupuy, N. Maitra 2024-07-15 ArXiv 0 32
visibility_off Solving forward and inverse PDE problems on unknown manifolds via physics-informed neural operators Anran Jiao, Qile Yan, Jhn Harlim, Lu Lu 2024-07-07 ArXiv 0 2
visibility_off Complex harmonics reveal low-dimensional manifolds of critical brain dynamics G. Deco, Y. Perl, M. Kringelbach 2024-06-16 bioRxiv 0 13
visibility_off Sampling metastable systems using collective variables and Jarzynski-Crooks paths Christoph Schonle, Marylou Gabri'e, T. Lelièvre, Gabriel Stoltz 2024-05-28 ArXiv 1 3
visibility_off Predicting solvation free energies with an implicit solvent machine learning potential Sebastien Rocken, A. F. Burnet, J. Zavadlav 2024-05-31 ArXiv 0 15
visibility_off Understanding the dynamics of the frequency bias in neural networks Juan Molina, Mircea Petrache, F. S. Costabal, Mat'ias Courdurier 2024-05-23 ArXiv 0 12
visibility_off Neural networks in non-metric spaces Luca Galimberti 2024-06-13 ArXiv 0 0
visibility_off Data-efficient fine-tuning of foundational models for first-principles quality sublimation enthalpies Harveen Kaur, Flaviano Della Pia, Ilyes Batatia, Xavier R Advincula, Benjamin X Shi, Jinggang Lan, G'abor Cs'anyi, A. Michaelides, V. Kapil 2024-05-30 ArXiv 0 75
visibility_off Invariant multiscale neural networks for data-scarce scientific applications I. Schurov, D. Alforov, M. Katsnelson, A. Bagrov, A. Itin 2024-06-12 ArXiv 0 0
visibility_off Efficient mapping of phase diagrams with conditional normalizing flows Maximilian Schebek, Michele Invernizzi, Frank No'e, Jutta Rogal 2024-06-18 ArXiv 0 2
visibility_off KAN-ODEs: Kolmogorov-Arnold Network Ordinary Differential Equations for Learning Dynamical Systems and Hidden Physics Benjamin C. Koenig, Suyong Kim, Sili Deng 2024-07-05 ArXiv 0 2
visibility_off Solving Poisson Equations using Neural Walk-on-Spheres Hong Chul Nam, Julius Berner, A. Anandkumar 2024-06-05 ArXiv 2 5
visibility_off Flow Map Matching Nicholas M. Boffi, M. S. Albergo, Eric Vanden-Eijnden 2024-06-11 ArXiv 0 16
visibility_off Inferring the time-varying coupling of dynamical systems with temporal convolutional autoencoders Josuan Calderon, Gordon J. Berman 2024-06-05 ArXiv 0 1
visibility_off DeepOKAN: Deep Operator Network Based on Kolmogorov Arnold Networks for Mechanics Problems D. Abueidda, Panos Pantidis, M. Mobasher 2024-05-29 ArXiv 7 24
visibility_off Fundamental limits of weak learnability in high-dimensional multi-index models Emanuele Troiani, Yatin Dandi, Leonardo Defilippis, Lenka Zdeborov'a, Bruno Loureiro, Florent Krzakala 2024-05-24 ArXiv 0 16
visibility_off Reduced-Order Neural Operators: Learning Lagrangian Dynamics on Highly Sparse Graphs Hrishikesh Viswanath, Yue Chang, Julius Berner, Peter Yichen Chen, Aniket Bera 2024-07-04 ArXiv 0 28
visibility_off Learning tensor trains from noisy functions with application to quantum simulation Kohtaroh Sakaue, H. Shinaoka, Rihito Sakurai 2024-05-21 ArXiv 0 21
visibility_off Benign overfitting in Fixed Dimension via Physics-Informed Learning with Smooth Inductive Bias Honam Wong, Wendao Wu, Fanghui Liu, Yiping Lu 2024-06-13 ArXiv 0 0
visibility_off Learning to Solve Multiresolution Matrix Factorization by Manifold Optimization and Evolutionary Metaheuristics T. Hy, Thieu Khang, R. Kondor 2024-06-01 ArXiv 0 30
visibility_off Poisson Variational Autoencoder Hadi Vafaii, Dekel Galor, Jacob L. Yates 2024-05-23 ArXiv 0 2
visibility_off State space reconstruction of Markov chains via autocorrelation structure Antal Jakovác, M. T. Kurbucz, András Telcs 2024-07-11 Journal of Physics A: Mathematical and Theoretical 0 6
visibility_off Message-Relevant Dimension Reduction of Neural Populations Amanda Merkley, Alice Y. Nam, Y. K. Hong, Pulkit Grover 2024-07-02 ArXiv 0 2
visibility_off Policy-guided Monte Carlo on general state spaces: Application to glass-forming mixtures Leonardo Galliano, Riccardo Rende, Daniele Coslovich 2024-07-03 ArXiv 0 0
visibility_off A Multiscale Perspective on Maximum Marginal Likelihood Estimation O. D. Akyildiz, M. Ottobre, I. Souttar 2024-06-06 ArXiv 2 11
visibility_off TrackSegNet: a tool for trajectory segmentation into diffusive states using supervised deep learning Hélène Kabbech, Ihor Smal 2024-06-04 Journal of Open Source Software 0 2
visibility_off WEDAP: A Python Package for Streamlined Plotting of Molecular Simulation Data Darian T. Yang, Lillian T. Chong 2024-05-21 bioRxiv 0 2
visibility_off Gaussian approximation of dynamic cavity equations for linearly-coupled stochastic dynamics Mattia Tarabolo, Luca Dall'Asta 2024-06-20 ArXiv 0 1
visibility_off Equivariant score-based generative diffusion framework for 3D molecules Hao Zhang, Yang Liu, Xiaoyan Liu, Cheng-Xiang Wang, Maozu Guo 2024-05-30 BMC Bioinformatics 0 17
visibility_off Spherinator and HiPSter: Representation Learning for Unbiased Knowledge Discovery from Simulations K. Polsterer, Bernd Doser, Andreas Fehlner, Sebastian Trujillo-Gomez 2024-06-06 ArXiv 0 15
visibility_off Stochastic Gradient Piecewise Deterministic Monte Carlo Samplers P. Fearnhead, Sebastiano Grazzi, Chris Nemeth, Gareth O. Roberts 2024-06-27 ArXiv 0 50
visibility_off Solving partial differential equations with sampled neural networks Chinmay Datar, Taniya Kapoor, Abhishek Chandra, Qing Sun, Iryna Burak, Erik Lien Bolager, Anna Veselovska, Massimo Fornasier, Felix Dietrich 2024-05-31 ArXiv 0 4
visibility_off Feature learning in finite-width Bayesian deep linear networks with multiple outputs and convolutional layers Federico Bassetti, M. Gherardi, Alessandro Ingrosso, M. Pastore, P. Rotondo 2024-06-05 ArXiv 1 14
visibility_off Modeling Randomly Observed Spatiotemporal Dynamical Systems V. Iakovlev, Harri Lähdesmäki 2024-06-01 ArXiv 0 2
visibility_off Efficient parameterization of transferable Atomic Cluster Expansion for water Eslam Ibrahim, Yu. Lysogorskiy, R. Drautz 2024-06-20 ArXiv 0 39
visibility_off Probing the effects of broken symmetries in machine learning Marcel F. Langer, S. Pozdnyakov, Michele Ceriotti 2024-06-25 ArXiv 0 9
visibility_off Decomposed Linear Dynamical Systems (dLDS) models reveal context-dependent dynamic connectivity in C. elegans Eva Yezerets, Noga Mudrik, Adam S. Charles 2024-06-01 bioRxiv 1 2
visibility_off Expressive Symbolic Regression for Interpretable Models of Discrete-Time Dynamical Systems Adarsh Iyer, N. Boddupalli, Jeff Moehlis 2024-06-05 ArXiv 0 5
visibility_off Disentangled representation learning with physics-informed variational autoencoder for structural health monitoring Ioannis Koune, Alice Cicirello 2024-07-01 e-Journal of Nondestructive Testing 0 1
visibility_off Dataset-learning duality and emergent criticality Ekaterina Kukleva, V. Vanchurin 2024-05-27 ArXiv 0 19
visibility_off BrowNNe: Brownian Nonlocal Neurons&Activation Functions Sriram Nagaraj, Truman Hickok 2024-06-21 ArXiv 0 0
visibility_off An efficient solution to Hidden Markov Models on trees with coupled branches. Farzan Vafa, S. Hormoz 2024-06-03 ArXiv 0 18
visibility_off CoNO: Complex Neural Operator for Continous Dynamical Physical Systems Karn Tiwari, N. M. A. Krishnan, P. PrathoshA 2024-06-01 ArXiv 0 0
visibility_off Dynamical Mean-Field Theory of Self-Attention Neural Networks 'Angel Poc-L'opez, Miguel Aguilera 2024-06-11 ArXiv 0 0
visibility_off Unraveling the where and when of coarse-grained entropy production: General theory meets single-molecule experiments Julius Degunther, Jann van der Meer, Udo Seifert 2024-05-28 ArXiv 0 1
visibility_off Estimating Free-Energy Surfaces and Their Convergence from Multiple, Independent Static and History-Dependent Biased Molecular-Dynamics Simulations with Mean Force Integration Antoniu Bjola, M. Salvalaglio 2024-06-24 Journal of Chemical Theory and Computation 0 25
visibility_off Deep learning of protein energy landscape and conformational dynamics from experimental structures in PDB Yike Tang, Mendi Yu, Ganggang Bai, Xinjun Li, Yanyan Xu, Buyong Ma 2024-06-27 bioRxiv 0 3
visibility_off Exact results on the dynamics of the stochastic Floquet-East model C. Fazio, J. P. Garrahan, Katja Klobas 2024-06-25 ArXiv 0 54
visibility_off Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network Hyunseok Oh, Youngki Lee 2024-07-01 ArXiv 0 3
visibility_off Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning D. Kunin, Allan Ravent'os, Cl'ementine Domin'e, Feng Chen, David Klindt, Andrew Saxe, Surya Ganguli 2024-06-10 ArXiv 1 12
visibility_off Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation Yididiya Y. Nadew, Xuhui Fan, Christopher J. Quinn 2024-05-19 ArXiv 0 1
visibility_off Comparing AI versus Optimization Workflows for Simulation-Based Inference of Spatial-Stochastic Systems Michael A. Ramirez-Sierra, T. Sokolowski 2024-07-15 ArXiv 0 7
visibility_off Deep neural networks with ReLU, leaky ReLU, and softplus activation provably overcome the curse of dimensionality for space-time solutions of semilinear partial differential equations Julia Ackermann, Arnulf Jentzen, Benno Kuckuck, J. Padgett 2024-06-16 ArXiv 0 45
visibility_off AdaFisher: Adaptive Second Order Optimization via Fisher Information Damien Martins Gomes, Yanlei Zhang, Eugene Belilovsky, Guy Wolf, Mahdi S. Hosseini 2024-05-26 ArXiv 0 7
visibility_off Lagrangian Neural Networks for Reversible Dissipative Evolution V. Sundararaghavan, Megna N. Shah, Jeff P. Simmons 2024-05-23 ArXiv 0 32
visibility_off Learning Diffusion at Lightspeed Antonio Terpin, Nicolas Lanzetti, Florian Dörfler 2024-06-18 ArXiv 0 10
visibility_off Variational autoencoder-based techniques for a streamlined cross-topology modeling and optimization workflow in electrical drives Marius Benkert, Michael Heroth, Rainer Herrler, Magda Gregorová, Helmut C. Schmid 2024-05-24 Auton. Intell. Syst. 0 1
visibility_off Training Dynamics of Nonlinear Contrastive Learning Model in the High Dimensional Limit Lineghuan Meng, Chuang Wang 2024-06-11 ArXiv 0 0
visibility_off Constructing coarse-grained models with physics-guided Gaussian process regression Yating Fang, Qian Qian Zhao, R. Sills, A. Ezzat 2024-06-01 APL Machine Learning 0 19
visibility_off Neural Network Representations of Multiphase Equations of State George A. Kevrekidis, Daniel A. Serino, Alexander Kaltenborn, J. Gammel, J. Burby, Marc L. Klasky 2024-06-28 ArXiv 0 16
visibility_off Orbital cluster-based network modelling A. Colanera, Nan Deng, M. Chiatto, Luigi De Luca, Bernd R. Noack 2024-07-01 ArXiv 0 12
visibility_off Density-Based Long-Range Electrostatic Descriptors for Machine Learning Force Fields Carolin Faller, Merzuk Kaltak, Georg Kresse 2024-06-25 ArXiv 0 15
visibility_off Efficient Probabilistic Modeling of Crystallization at Mesoscopic Scale Pol Timmer, Koen Minartz, V. Menkovski 2024-05-26 ArXiv 0 7
visibility_off ULTRA-MC: A Unified Approach to Learning Mixtures of Markov Chains via Hitting Times Fabian Spaeh, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis 2024-05-23 ArXiv 0 32
visibility_off Representation and De-interleaving of Mixtures of Hidden Markov Processes Jiadi Bao, Mengtao Zhu, Yunjie Li, Shafei Wang 2024-06-01 ArXiv 0 11
visibility_off A scale-similarity based workflow for self-supervised reconstruction of small-scales in turbulence using deep learning Priyabrat Dash, K. Aditya 2024-07-01 Physics of Fluids 0 8
visibility_off On Regularization via Early Stopping for Least Squares Regression Rishi Sonthalia, Jackie Lok, E. Rebrova 2024-06-06 ArXiv 0 9
visibility_off Metric-Entropy Limits on Nonlinear Dynamical System Learning Yang Pan, Clemens Hutter, Helmut Bolcskei 2024-07-01 ArXiv 0 2
visibility_off Iterative Methods for Full-Scale Gaussian Process Approximations for Large Spatial Data Tim Gyger, Reinhard Furrer, Fabio Sigrist 2024-05-23 ArXiv 0 0
visibility_off FUSE: Fast Unified Simulation and Estimation for PDEs Levi E. Lingsch, Dana Grund, Siddhartha Mishra, Georgios Kissas 2024-05-23 ArXiv 0 1
visibility_off Assessing the Accuracy and Efficiency of Free Energy Differences Obtained from Reweighted Flow-Based Probabilistic Generative Models. Edgar Olehnovics, Yifei Michelle Liu, Nada Mehio, Ahmad Y Sheikh, Michael R. Shirts, M. Salvalaglio 2024-07-10 Journal of chemical theory and computation 1 46
visibility_off Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows A. Cabezas, Louis Sharrock, Christopher Nemeth 2024-05-23 ArXiv 0 3
visibility_off Pi-fusion: Physics-informed diffusion model for learning fluid dynamics Jing Qiu, Jiancheng Huang, Xiangdong Zhang, Zeng Lin, Minglei Pan, Zengding Liu, F. Miao 2024-06-06 ArXiv 1 20
visibility_off On the Mode-Seeking Properties of Langevin Dynamics Xiwei Cheng, Kexin Fu, Farzan Farnia 2024-06-04 ArXiv 0 10
visibility_off Ensemble and Mixture-of-Experts DeepONets For Operator Learning Ramansh Sharma, Varun Shankar 2024-05-20 ArXiv 0 2
visibility_off Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior Anming Gu, Edward Chien, K. Greenewald 2024-06-11 ArXiv 0 20
visibility_off HiPPO-Prophecy: State-Space Models can Provably Learn Dynamical Systems in Context Federico Arangath Joseph, K. Haefeli, Noah Liniger, Caglar Gulcehre 2024-07-12 ArXiv 0 3
visibility_off On the dynamics of convolutional recurrent neural networks near their critical point Aditi Chandra, M. Magnasco 2024-05-22 ArXiv 1 42
visibility_off Neural Persistence Dynamics Sebastian Zeng, Florian Graf, M. Uray, Stefan Huber, R. Kwitt 2024-05-24 ArXiv 0 32
visibility_off Exploiting Chaotic Dynamics as Deep Neural Networks Shuhong Liu, Nozomi Akashi, Qingyao Huang, Yasuo Kuniyoshi, Kohei Nakajima 2024-05-29 ArXiv 1 8
visibility_off Stable Weight Updating: A Key to Reliable PDE Solutions Using Deep Learning A. Noorizadegan, R. Cavoretto, D. Young, C. S. Chen 2024-07-10 ArXiv 0 4
visibility_off Towards Universal Unfolding of Detector Effects in High-Energy Physics using Denoising Diffusion Probabilistic Models Camila Pazos, Shuchin Aeron, P. Beauchemin, Vincent Croft, Martin Klassen, Taritree Wongjirad 2024-06-03 ArXiv 0 41
visibility_off Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions Luca Arnaboldi, Yatin Dandi, Florent Krzakala, Luca Pesce, Ludovic Stephan 2024-05-24 ArXiv 1 9
visibility_off Physics-constrained learning for PDE systems with uncertainty quantified port-Hamiltonian models Kaiyuan Tan, Peilun Li, Thomas Beckers 2024-06-17 DBLP, ArXiv 0 1
visibility_off Active search for Bifurcations Y. M. Psarellis, T. Sapsis, I. G. Kevrekidis 2024-06-17 ArXiv 0 37
visibility_off Non-convergence of Adam and other adaptive stochastic gradient descent optimization methods for non-vanishing learning rates Steffen Dereich, Robin Graeber, Arnulf Jentzen 2024-07-11 ArXiv 0 45
visibility_off Marrying Causal Representation Learning with Dynamical Systems for Science Dingling Yao, Caroline Muller, Francesco Locatello 2024-05-22 ArXiv 0 9
visibility_off Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks Felix Dangel, Johannes Müller, Marius Zeinhofer 2024-05-24 ArXiv 0 6
visibility_off The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models S. Kandasamy, Dheeraj M. Nagaraj 2024-05-27 ArXiv 1 13
visibility_off Integrating GNN and Neural ODEs for Estimating Two-Body Interactions in Mixed-Species Collective Motion Masahito Uwamichi, S. Schnyder, Tetsuya J. Kobayashi, Satoshi Sawai 2024-05-26 ArXiv 0 10
visibility_off Reinforcement Learning for Adaptive MCMC Congye Wang, Wilson Chen, Heishiro Kanagawa, C. Oates 2024-05-22 ArXiv 1 24
visibility_off On Dissipativity of Cross-Entropy Loss in Training ResNets Jens Püttschneider, T. Faulwasser 2024-05-29 ArXiv 0 28
visibility_off On the Definition of Velocity in Discrete-Time, Stochastic Langevin Simulations Niels Gronbech-Jensen 2024-05-25 ArXiv 0 0
visibility_off Joint Learning of Linear Dynamical Systems under Smoothness Constraints Hemant Tyagi 2024-06-03 ArXiv 0 0
visibility_off Enhancing the Prediction of Glass Dynamics by Incorporating the Direction of Deviation from Equilibrium Positions Xiao Jiang, Zean Tian, Kenli Li, Wangyu Hu 2024-07-08 ArXiv 0 7
visibility_off The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms Elizabeth Collins-Woodfin, Inbar Seroussi, Begona Garc'ia Malaxechebarr'ia, Andrew W. Mackenzie, Elliot Paquette, Courtney Paquette 2024-05-30 ArXiv 0 6
visibility_off Time Series Clustering with General State Space Models via Stochastic Variational Inference Ryoichi Ishizuka, Takashi Imai, Kaoru Kawamoto 2024-06-29 ArXiv 0 0
visibility_off Complete realization of energy landscapes and non-equilibrium trapping dynamics in small spin glass and optimization problems H. Po, Chi Ho Yeung 2024-07-08 Scientific Reports 0 2
visibility_off Causal inference through multi-stage learning and doubly robust deep neural networks Yuqian Zhang, Jelena Bradic 2024-07-11 ArXiv 0 1
visibility_off Latent Variable Sequence Identification for Cognitive Models with Neural Bayes Estimation Ti-Fen Pan, Jing-Jing Li, Bill Thompson, Anne Collins 2024-06-20 ArXiv 0 1
visibility_off Prediction of Unobserved Bifurcation by Unsupervised Extraction of Slowly Time-Varying System Parameter Dynamics from Time Series Using Reservoir Computing Keita Tokuda, Yuichi Katori 2024-06-20 ArXiv 0 10
visibility_off Glassy dynamics in deep neural networks: A structural comparison Max Kerr Winter, Liesbeth M. C. Janssen 2024-05-21 ArXiv 0 0
visibility_off Unlocking Guidance for Discrete State-Space Diffusion and Flow Models Hunter Nisonoff, Junhao Xiong, Stephan Allenspach, Jennifer Listgarten 2024-06-03 ArXiv 0 6
visibility_off Lattice physics approaches for neural networks G. Bardella, Simone Franchini, P. Pani, S. Ferraina 2024-05-20 ArXiv 0 35
visibility_off Convolutional dynamical sampling and some new results Longxiu Huang, A. M. Neuman, Sui Tang, Yuying Xie 2024-06-21 ArXiv 0 0
visibility_off Faster Sampling via Stochastic Gradient Proximal Sampler Xunpeng Huang, Difan Zou, Yian Ma, Hanze Dong, Tong Zhang 2024-05-27 ArXiv 0 14
visibility_off Hidden Markov models with an unknown number of states and a repulsive prior on the state parameters Ioannis Rotous, Alex Diana, Alessio Farcomeni, Eleni Material, Andr'ea Thiebault 2024-07-15 ArXiv 0 2
visibility_off Constructive Function Approximation with Local Models Christos N. Mavridis, K. H. Johansson 2024-06-11 2024 32nd Mediterranean Conference on Control and Automation (MED) 0 0
visibility_off Exact Gauss-Newton Optimization for Training Deep Neural Networks Mikalai Korbit, Adeyemi Damilare Adeoye, Alberto Bemporad, Mario Zanon 2024-05-23 ArXiv 0 2
visibility_off A Gaussian Process-based Streaming Algorithm for Prediction of Time Series With Regimes and Outliers Daniel Waxman, Petar M. Djuri'c 2024-06-01 ArXiv 0 1
visibility_off Balancing Molecular Information and Empirical Data in the Prediction of Physico-Chemical Properties Johannes Zenn, Dominik Gond, F. Jirasek, Robert Bamler 2024-06-12 ArXiv 0 14
visibility_off How Inductive Bias in Machine Learning Aligns with Optimality in Economic Dynamics Mahdi Ebrahimi Kahou, James Yu, Jesse Perla, Geoff Pleiss 2024-06-04 ArXiv 0 2
visibility_off Conditional score-based diffusion models for solving inverse problems in mechanics Agnimitra Dasgupta, Harisankar Ramaswamy, J. M. Esandi, Ken Foo, Runze Li, Qifa Zhou, Brendan Kennedy, Assad Oberai 2024-06-19 ArXiv 0 14
visibility_off Hamilton-Jacobi Based Policy-Iteration via Deep Operator Learning Jae Yong Lee, Yeoneung Kim 2024-06-16 ArXiv 1 5
visibility_off Warm Start Marginal Likelihood Optimisation for Iterative Gaussian Processes J. Lin, S. Padhy, Bruno Mlodozeniec, Jos'e Miguel Hern'andez-Lobato 2024-05-28 ArXiv 0 3
visibility_off Evaluating the design space of diffusion-based generative models Yuqing Wang, Ye He, Molei Tao 2024-06-18 ArXiv 0 1
visibility_off Self-consistent Coulomb interactions for machine learning interatomic potentials Jack Thomas, William J. Baldwin, G'abor Cs'anyi, Christoph Ortner 2024-06-16 ArXiv 0 3
visibility_off Laplacian Renormalization Group: An introduction to heterogeneous coarse-graining Guido Caldarelli, A. Gabrielli, Tommaso Gili, Pablo Villegas 2024-06-04 ArXiv 0 12
visibility_off Temporal Convolution Derived Multi-Layered Reservoir Computing Johannes Viehweg, Dominik Walther, Prof. Dr.-Ing. Patrick Mader 2024-07-09 ArXiv 0 2
visibility_off The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof Derek Lim, Moe Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka 2024-05-30 ArXiv 0 23
visibility_off Knowledge-Guided Learning of Temporal Dynamics and its Application to Gas Turbines Pawel Bielski, Aleksandr Eismont, Jakob Bach, Florian Leiser, D. Kottonau, Klemens Böhm 2024-05-31 Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems 0 8
visibility_off Bartender: Martini 3 Bonded Terms via Quantum Mechanics-Based Molecular Dynamics. Gilberto P. Pereira, Riccardo Alessandri, Moisés Domínguez, Rocío Araya-Osorio, Linus Grünewald, Luís Borges-Araújo, Sangwook Wu, Siewert J. Marrink, Paulo C. T. Souza, Raúl Mera-Adasme 2024-06-26 Journal of chemical theory and computation 0 19
visibility_off Computing hydration free energies of small molecules with first principles accuracy J. H. Moore, Daniel J. Cole, Gábor Csányi 2024-05-28 ArXiv 0 2
visibility_off Deep linear networks for regression are implicitly regularized towards flat minima Pierre Marion, L'enaic Chizat 2024-05-22 ArXiv 1 1
visibility_off Learning dynamical models from stochastic trajectories Pierre Ronceray 2024-06-04 ArXiv 0 0
visibility_off Physics informed cell representations for variational formulation of multiscale problems Yuxiang Gao, Soheil Kolouri, R. Duddu 2024-05-27 ArXiv 0 28
visibility_off Separation Power of Equivariant Neural Networks Marco Pacini, Xiaowen Dong, Bruno Lepri, G. Santin 2024-06-13 ArXiv 0 5
visibility_off The dynamics of machine-learned"softness"in supercooled liquids describe dynamical heterogeneity S. Ridout, Andrea J. Liu 2024-06-09 ArXiv 0 8
visibility_off Amortized Equation Discovery in Hybrid Dynamical Systems Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, E. Gavves 2024-06-06 ArXiv 0 36
visibility_off Probabilistic response determination of high-dimensional nonlinear dynamical systems enforced by parametric multiple Poisson white noises Jian-Bing Chen, Meng-Ze Lyu 2024-05-20 Nonlinear Dynamics 0 7
visibility_off Consistency Models Made Easy Zhengyang Geng, Ashwini Pokle, William Luo, Justin Lin, J. Z. Kolter 2024-06-20 ArXiv 0 59
visibility_off Stability and Generalizability in SDE Diffusion Models with Measure-Preserving Dynamics Weitong Zhang, Chengqi Zang, Liu Li, Sarah Cechnicka, Ouyang Cheng, Bernhard Kainz 2024-06-19 ArXiv 0 1
visibility_off Low-resolution descriptions of model neural activity reveal hidden features and underlying system properties Riccardo Aldrigo, R. Menichetti, R. Potestio 2024-05-23 ArXiv 0 24
visibility_off Unsupervised machine learning for detecting mutual independence among eigenstate regimes in interacting quasiperiodic chains Colin Beveridge, Cassio Cristani, Xiao Li, Enrico Barbierato, Yi-Ting Hsu 2024-07-08 ArXiv 0 2
visibility_off ArcaNN: automated enhanced sampling generation of training sets for chemically reactive machine learning interatomic potentials Rolf David, Miguel de la Puente, Axel Gomez, Olaia Anton, Guillaume Stirnemann, Damien Laage Pasteur, D'epartement de Chimie, 'Ecole Normale Sup'erieure, P. university, Sorbonne University, Cnrs, Paris 2024-07-10 ArXiv 0 52
visibility_off Proximal Interacting Particle Langevin Algorithms Paula Cordero Encinar, F. R. Crucinio, O. D. Akyildiz 2024-06-20 ArXiv 1 6
visibility_off An approach to non-equilibrium statistical physics using variational Bayesian inference M. Ramstead, D. A. R. Sakthivadivel, K. Friston 2024-06-17 ArXiv 0 23
visibility_off Error Analysis of Three-Layer Neural Network Trained with PGD for Deep Ritz Method Yuling Jiao, Yanming Lai, Yang Wang 2024-05-19 ArXiv 0 6
visibility_off APTT: An accuracy-preserved tensor-train method for the Boltzmann-BGK equation Zhitao Zhu, Chuanfu Xiao, Keju Tang, Jizu Huang, Chao Yang 2024-05-21 ArXiv 0 7
visibility_off Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics Jonas Spinner, Victor Bres'o, P. D. Haan, Tilman Plehn, Jesse Thaler, Johann Brehmer 2024-05-23 ArXiv 2 13
visibility_off Long Short-term Cognitive Networks: An Empirical Performance Study Gonzalo Nápoles, Isel Grau 2024-05-23 2024 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) 0 13
visibility_off A Study of Posterior Stability for Time-Series Latent Diffusion Yangming Li, M. Schaar 2024-05-22 ArXiv 0 64
visibility_off Adaptive energy reference for machine-learning models of the electronic density of states Wei Bin How, Sanggyu Chong, Federico Grasselli, Kevin K. Huguenin-Dumittan, Michele Ceriotti 2024-07-01 ArXiv 0 2
visibility_off Application of physics encoded neural networks to improve predictability of properties of complex multi-scale systems M. Meinders, Jack Yang, Erik van der Linden 2024-07-01 Scientific Reports 0 29
visibility_off Latent Intuitive Physics: Learning to Transfer Hidden Physics from A 3D Video Xiangming Zhu, Huayu Deng, Haochen Yuan, Yunbo Wang, Xiaokang Yang 2024-06-18 ArXiv 0 6
visibility_off Model-Based Diffusion for Trajectory Optimization Chaoyi Pan, Zeji Yi, Guanya Shi, Guannan Qu 2024-05-28 ArXiv 1 1
visibility_off Early stopping for conjugate gradients in statistical inverse problems Laura Hucker, Markus Reiss 2024-06-21 ArXiv 0 0
visibility_off Gradient matching accelerates mixed-effects inference for biochemical networks Yulan B van Oppen, Andreas Milias-Argeitis 2024-06-12 bioRxiv 0 15
visibility_off Gradients of Functions of Large Matrices Nicholas Krämer, Pablo Moreno-Munoz, Hrittik Roy, Søren Hauberg 2024-05-27 ArXiv 0 8
visibility_off Sampling From Multiscale Densities With Delayed Rejection Generalized Hamiltonian Monte Carlo Gilad Turok, Chirag Modi, Bob Carpenter 2024-06-04 ArXiv 0 0
visibility_off Inference for the stochastic FitzHugh-Nagumo model from real action potential data via approximate Bayesian computation Adeline Samson, M. Tamborrino, I. Tubikanec 2024-05-28 ArXiv 0 11
visibility_off H-Fac: Memory-Efficient Optimization with Factorized Hamiltonian Descent Son Nguyen, Lizhang Chen, Bo Liu, Qiang Liu 2024-06-14 ArXiv 0 1
visibility_off Role of correlations in the maximum distribution of multiscale stationary Markovian processes Salvatore Micciche 2024-05-19 ArXiv 0 0
visibility_off Flow Perturbation to Accelerate Unbiased Sampling of Boltzmann distribution Xin Peng, Ang Gao 2024-07-15 ArXiv 0 0
visibility_off Towards stable training of parallel continual learning Yuepan Li, Fan Lyu, Yuyang Li, Wei Feng, Guangcan Liu, Fanhua Shang 2024-07-11 ArXiv 0 2
visibility_off Markov Switching Multiple-equation Tensor Regressions Roberto Casarin, Radu V. Craiu, Qing Wang 2024-06-30 ArXiv 0 20
visibility_off Generative Diffusion Models for Fast Simulations of Particle Collisions at CERN Mikolaj Kita, Jan Dubi'nski, Przemyslaw Rokita, K. Deja 2024-06-05 ArXiv 0 29
visibility_off Learning Force Field Parameters from Differentiable Particle-Field Molecular Dynamics. Manuel Carrer, H. M. Cezar, S. Bore, Morten Ledum, Michele Cascella 2024-07-04 Journal of chemical information and modeling 0 11
visibility_off Thermodynamic Natural Gradient Descent Kaelan Donatella, Samuel Duffield, Maxwell Aifer, Denis Melanson, Gavin Crooks, Patrick J. Coles 2024-05-22 ArXiv 0 4
visibility_off Demystifying SGD with Doubly Stochastic Gradients Kyurae Kim, Joohwan Ko, Yian Ma, Jacob R. Gardner 2024-06-03 ArXiv 0 6
visibility_off Recurrent Stochastic Configuration Networks for Temporal Data Analytics Dianhui Wang, Gang Dang 2024-06-21 ArXiv 0 1
visibility_off Solving Inverse Problems in Protein Space Using Diffusion-Based Priors A. Levy, E. R. Chan, Sara Fridovich-Keil, Frédéric Poitevin, Ellen D. Zhong, Gordon Wetzstein 2024-06-06 ArXiv 0 7
visibility_off Scalable Optimization in the Modular Norm Tim Large, Yang Liu, Minyoung Huh, Hyojin Bahng, Phillip Isola, Jeremy Bernstein 2024-05-23 ArXiv 0 9
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index