Noisy Recurrent Neural Networks

9 February 2021

Papers citing "Noisy Recurrent Neural Networks"

50 / 64 papers shown

Title
Robust Asymmetric Heterogeneous Federated Learning with Corrupted Clients Xiuwen Fang Mang Ye Di Lin FedML 161 1 0 12 Mar 2025
MeMo: Meaningful, Modular Controllers via Noise Injection Megan Tjandrasuwita Jie Xu Armando Solar-Lezama Wojciech Matusik 59 0 0 24 May 2024
Gated Recurrent Neural Networks with Weighted Time-Delay Feedback N. Benjamin Erichson Soon Hoe Lim Michael W. Mahoney 63 6 0 01 Dec 2022
On the Origin of Implicit Regularization in Stochastic Gradient Descent Samuel L. Smith Benoit Dherin David Barrett Soham De MLT 36 203 0 28 Jan 2021
Implicit Bias of Linear RNNs M Motavali Emami Mojtaba Sahraee-Ardakan Parthe Pandit S. Rangan A. Fletcher 39 11 0 19 Jan 2021
Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies T. Konstantin Rusch Siddhartha Mishra 112 92 0 02 Oct 2020
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't E. Weinan Chao Ma Stephan Wojtowytsch Lei Wu AI4CE 69 134 0 22 Sep 2020
Continuous-in-Depth Neural Networks A. Queiruga N. Benjamin Erichson D. Taylor Michael W. Mahoney 58 47 0 05 Aug 2020
Explicit Regularisation in Gaussian Noise Injections A. Camuto M. Willetts Umut Simsekli Stephen J. Roberts Chris Holmes 47 59 0 14 Jul 2020
On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools Ryan H. Vogt M. P. Touzel Eli Shlizerman Guillaume Lajoie 66 42 0 25 Jun 2020
Lipschitz Recurrent Neural Networks N. Benjamin Erichson Omri Azencot A. Queiruga Liam Hodgkinson Michael W. Mahoney 67 111 0 22 Jun 2020
Understanding Recurrent Neural Networks Using Nonequilibrium Response Theory Soon Hoe Lim 70 16 0 19 Jun 2020
Deep Adversarial Koopman Model for Reaction-Diffusion systems K. Balakrishnan Devesh Upadhyay 48 5 0 09 Jun 2020
Do RNN and LSTM have Long Memory? Jingyu Zhao Feiqing Huang Jia Lv Yanjie Duan Zhen Qin Guodong Li Guangjian Tian 94 143 0 06 Jun 2020
Optimizing Neural Networks via Koopman Operator Theory Akshunna S. Dogra William T. Redman 50 51 0 03 Jun 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 101 472 0 18 May 2020
The Implicit Regularization of Stochastic Gradient Flow for Least Squares Alnur Ali Yan Sun Robert Tibshirani 65 77 0 17 Mar 2020
Dropout: Explicit Forms and Capacity Control R. Arora Peter L. Bartlett Poorya Mianjy Nathan Srebro 96 38 0 06 Mar 2020
Forecasting Sequential Data using Consistent Koopman Autoencoders Omri Azencot N. Benjamin Erichson Vanessa Lin Michael W. Mahoney AI4TS AI4CE 153 149 0 04 Mar 2020
The Implicit and Explicit Regularization Effects of Dropout Colin Wei Sham Kakade Tengyu Ma 80 117 0 28 Feb 2020
Disentangling Trainability and Generalization in Deep Neural Networks Lechao Xiao Jeffrey Pennington S. Schoenholz 51 34 0 30 Dec 2019
Machine Learning from a Continuous Viewpoint E. Weinan Chao Ma Lei Wu 106 104 0 30 Dec 2019
Exact expressions for double descent and implicit regularization via surrogate random design Michal Derezinski Feynman T. Liang Michael W. Mahoney 55 78 0 10 Dec 2019
Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families Yibo Yang Jianlong Wu Hongyang Li Xia Li Tiancheng Shen Zhouchen Lin OOD 36 21 0 23 Nov 2019
Learning Compositional Koopman Operators for Model-Based Control Yunzhu Li Hao He Jiajun Wu Dina Katabi Antonio Torralba 92 119 0 18 Oct 2019
Hamiltonian Generative Networks Peter Toth Danilo Jimenez Rezende Andrew Jaegle S. Racanière Aleksandar Botev I. Higgins BDL DRL AI4CE GAN 61 217 0 30 Sep 2019
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 209 225 0 29 Sep 2019
Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN 88 271 0 26 Sep 2019
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning M. Lutter Christian Ritter Jan Peters PINN AI4CE 58 378 0 10 Jul 2019
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks Kaifeng Lyu Jian Li 81 335 0 13 Jun 2019
Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed Stability Shaowu Pan Karthik Duraisamy 60 138 0 09 Jun 2019
Hamiltonian Neural Networks S. Greydanus Misko Dzamba J. Yosinski PINN AI4CE 118 894 0 04 Jun 2019
Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction N. Benjamin Erichson Michael Muehlebach Michael W. Mahoney AI4CE PINN 56 141 0 26 May 2019
Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit Belinda Tzen Maxim Raginsky DiffM 164 209 0 23 May 2019
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation Colin Wei Tengyu Ma 59 110 0 09 May 2019
Towards Robust ResNet: A Small Step but A Giant Leap Jingfeng Zhang Bo Han L. Wynter K. H. Low Mohan Kankanhalli 50 41 0 28 Feb 2019
Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control Jeremy Morton F. Witherden Mykel J Kochenderfer 54 47 0 26 Feb 2019
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks B. Chang Minmin Chen E. Haber Ed H. Chi PINN GNN 102 204 0 26 Feb 2019
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group Mario Lezcano Casado David Martínez-Rubio 48 200 0 24 Jan 2019
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 260 280 0 03 Dec 2018
Stochastic Training of Residual Networks: a Differential Equation Viewpoint Qi Sun Yunzhe Tao Q. Du 47 24 0 01 Dec 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 411 5,103 0 19 Jun 2018
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks Minmin Chen Jeffrey Pennington S. Schoenholz SyDa AI4CE 52 116 0 14 Jun 2018
Stable Recurrent Models John Miller Moritz Hardt 51 119 0 25 May 2018
Noisin: Unbiased Regularization for Recurrent Neural Networks Adji Bousso Dieng Rajesh Ranganath Jaan Altosaar David M. Blei 50 22 0 03 May 2018
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries Z. Yao A. Gholami Qi Lei Kurt Keutzer Michael W. Mahoney 63 167 0 22 Feb 2018
Theory of Deep Learning III: explaining the non-overfitting puzzle T. Poggio Kenji Kawaguchi Q. Liao Brando Miranda Lorenzo Rosasco Xavier Boix Jack Hidary H. Mhaskar ODL 55 128 0 30 Dec 2017
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations Yiping Lu Aoxiao Zhong Quanzheng Li Bin Dong 210 503 0 27 Oct 2017
Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization Hyeonwoo Noh Tackgeun You Jonghwan Mun Bohyung Han NoLa 61 199 0 14 Oct 2017
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition Naoya Takeishi Yoshinobu Kawahara Takehisa Yairi 46 370 0 12 Oct 2017