Generative learning for nonlinear dynamics

7 November 2023

Papers citing "Generative learning for nonlinear dynamics"

47 / 47 papers shown

Title
How more data can hurt: Instability and regularization in next-generation reservoir computing Yuanzhao Zhang Edmilson Roque dos Santos Sean P. Cornelius 153 2 0 28 Jan 2025
Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data Manuel Brenner Elias Weber G. Koppe Daniel Durstewitz AI4TS AI4CE 111 8 0 07 Oct 2024
Measuring and Controlling Solution Degeneracy across Task-Trained Recurrent Neural Networks Ann Huang Satpreet H. Singh Flavio Martinelli Kanaka Rajan 88 0 0 04 Oct 2024
Zero-shot forecasting of chaotic systems Yuanzhao Zhang William Gilpin AI4TS 249 8 0 24 Sep 2024
Machine learning in and out of equilibrium Shishir Adhikari Alkan Kabakcciouglu A. Strang Deniz Yuret M. Hinczewski 60 5 0 06 Jun 2023
Complexity-calibrated Benchmarks for Machine Learning Reveal When Next-Generation Reservoir Computer Predictions Succeed and Mislead Sarah E. Marzen P. Riechers James P. Crutchfield 86 2 0 25 Mar 2023
Transformers Learn Shortcuts to Automata Bingbin Liu Jordan T. Ash Surbhi Goel A. Krishnamurthy Cyril Zhang OffRL LRM 159 178 0 19 Oct 2022
Manifold Interpolating Optimal-Transport Flows for Trajectory Inference G. Huguet D. S. Magruder Alexander Tong O. Fasina Manik Kuchroo Guy Wolf Smita Krishnaswamy OT DRL 121 65 0 29 Jun 2022
Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics Noga Mudrik Yenho Chen Eva Yezerets Christopher Rozell Adam S. Charles 87 16 0 07 Jun 2022
Fundamental limits to learning closed-form mathematical models from data Oscar Fajardo-Fontiveros I. Reichardt Harry R. De Los Ríos Jordi Duch Marta Sales-Pardo Roger Guimerà 83 19 0 06 Apr 2022
Training Compute-Optimal Large Language Models Jordan Hoffmann Sebastian Borgeaud A. Mensch Elena Buchatskaya Trevor Cai ... Karen Simonyan Erich Elsen Jack W. Rae Oriol Vinyals Laurent Sifre AI4TS 211 1,988 0 29 Mar 2022
Data-Driven Modeling and Prediction of Non-Linearizable Dynamics via Spectral Submanifolds Mattia Cenedese Joar Axås Bastian Bäuerlein Kerstin Avila George Haller 81 127 0 13 Jan 2022
On the difficulty of learning chaotic dynamics with RNNs Jonas M. Mikhaeil Zahra Monfared Daniel Durstewitz 123 59 0 14 Oct 2021
Chaos as an interpretable benchmark for forecasting and data-driven modelling W. Gilpin AI4TS 65 82 0 11 Oct 2021
Data-driven discovery of intrinsic dynamics D. Floryan M. Graham AI4CE 171 77 0 12 Aug 2021
Multi-Facet Clustering Variational Autoencoders Fabian Falck Haoting Zhang M. Willetts G. Nicholson C. Yau Chris Holmes DRL 69 44 0 09 Jun 2021
Modern Koopman Theory for Dynamical Systems Steven L. Brunton M. Budišić E. Kaiser J. Nathan Kutz AI4CE 122 420 0 24 Feb 2021
Forecasting: theory and practice F. Petropoulos D. Apiletti Vassilios Assimakopoulos M. Z. Babai Devon K. Barrow ... J. Arenas Xiaoqian Wang R. L. Winkler Alisa Yusupova F. Ziel AI4TS 115 373 0 04 Dec 2020
Do Reservoir Computers Work Best at the Edge of Chaos? T. Carroll 48 63 0 02 Dec 2020
Neural-Symbolic Integration: A Compositional Perspective Efthymia Tsamoura Loizos Michael NAI 91 69 0 22 Oct 2020
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 522 2,456 0 18 Oct 2020
Dynamical Variational Autoencoders: A Comprehensive Review Laurent Girin Simon Leglaive Xiaoyu Bie Julien Diard Thomas Hueber Xavier Alameda-Pineda BDL 130 219 0 28 Aug 2020
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity S. Udrescu A. Tan Jiahai Feng Orisvaldo Neto Tailin Wu Max Tegmark 113 193 0 18 Jun 2020
Deep learning to discover and predict dynamics on an inertial manifold Alec J. Linot M. Graham AI4CE 55 75 0 20 Dec 2019
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems E. Qian Boris Kramer Benjamin Peherstorfer Karen E. Willcox AI4CE 111 267 0 17 Dec 2019
Learning Deterministic Weighted Automata with Queries and Counterexamples Gail Weiss Yoav Goldberg Eran Yahav TPM 93 45 0 30 Oct 2019
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 248 2,162 0 08 Oct 2019
Learning the Tangent Space of Dynamical Instabilities from Data Antoine Blanchard T. Sapsis 134 8 0 24 Jul 2019
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 260 3,962 0 12 Jul 2019
Hamiltonian Neural Networks S. Greydanus Misko Dzamba J. Yosinski PINN AI4CE 135 899 0 04 Jun 2019
Augmented Neural ODEs Emilien Dupont Arnaud Doucet Yee Whye Teh BDL 159 634 0 02 Apr 2019
Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI G. Koppe Hazem Toutounji P. Kirsch S. Lis Daniel Durstewitz MedIm 71 79 0 19 Feb 2019
Recent Advances in Autoencoder-Based Representation Learning Michael Tschannen Olivier Bachem Mario Lucic OOD SSL DRL 83 446 0 12 Dec 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 463 5,176 0 19 Jun 2018
Deep learning for universal linear embeddings of nonlinear dynamics Bethany Lusch J. Nathan Kutz Steven L. Brunton 83 1,261 0 27 Dec 2017
Neural Discrete Representation Learning Aaron van den Oord Oriol Vinyals Koray Kavukcuoglu BDL SSL OCL 255 5,082 0 02 Nov 2017
Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics C. Wehmeyer Frank Noé AI4CE BDL 167 361 0 30 Oct 2017
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition Naoya Takeishi Yoshinobu Kawahara Takehisa Yairi 51 374 0 12 Oct 2017
Structure and Randomness of Continuous-Time Discrete-Event Processes Sarah E. Marzen James P. Crutchfield 43 27 0 16 Apr 2017
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 367 5,390 0 03 Nov 2016
Exponential expressivity in deep neural networks through transient chaos Ben Poole Subhaneil Lahiri M. Raghu Jascha Narain Sohl-Dickstein Surya Ganguli 100 596 0 16 Jun 2016
Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models Viktoriya Krakovna Finale Doshi-Velez AI4CE 150 69 0 16 Jun 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 340 4,817 0 04 Jan 2016
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 315 7,035 0 12 Mar 2015
Semi-Supervised Learning with Deep Generative Models Diederik P. Kingma Danilo Jimenez Rezende S. Mohamed Max Welling GAN SSL BDL 107 2,746 0 20 Jun 2014
On the Number of Linear Regions of Deep Neural Networks Guido Montúfar Razvan Pascanu Kyunghyun Cho Yoshua Bengio 98 1,256 0 08 Feb 2014
Testing the Manifold Hypothesis Charles Fefferman S. Mitter Hariharan Narayanan 170 537 0 01 Oct 2013