Stable Architectures for Deep Neural Networks

9 May 2017

Papers citing "Stable Architectures for Deep Neural Networks"

50 / 143 papers shown

Title
Zero Stability Well Predicts Performance of Convolutional Neural Networks Liangming Chen Long Jin Mingsheng Shang MLT 24 8 0 27 Jun 2022
Learning the parameters of a differential equation from its trajectory via the adjoint equation I. Fekete A. Molnár P. Simon 13 0 0 17 Jun 2022
Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules Kazuki Irie Francesco Faccio Jürgen Schmidhuber AI4TS 38 11 0 03 Jun 2022
Standalone Neural ODEs with Sensitivity Analysis Rym Jaroudi Lukáš Malý Gabriel Eilertsen B. Johansson Jonas Unger George Baravdish 23 0 0 27 May 2022
Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics Xin-Yang Liu Min Zhu Lu Lu Hao Sun Jian-Xun Wang PINN AI4CE 36 45 0 09 May 2022
Path Development Network with Finite-dimensional Lie Group Representation Han Lou Siran Li Hao Ni 18 7 0 02 Apr 2022
$$\ell_1$DecNet+: A new architecture framework by $\ell_1$ decomposition and iteration unfolding for sparse feature segmentation$ $\ell_1$ DecNet+: A new architecture framework by $\ell_1$ decomposition and iteration unfolding for sparse feature segmentation Yumeng Ren Yiming Gao Chunlin Wu Bergen 23 3 0 05 Mar 2022
Neural Ordinary Differential Equations for Nonlinear System Identification Aowabin Rahman Ján Drgoňa Aaron Tuor J. Strube 25 22 0 28 Feb 2022
LyaNet: A Lyapunov Framework for Training Neural ODEs I. D. Rodriguez Aaron D. Ames Yisong Yue 33 51 0 05 Feb 2022
Graph-Coupled Oscillator Networks T. Konstantin Rusch B. Chamberlain J. Rowbottom S. Mishra M. Bronstein 42 105 0 04 Feb 2022
On the Stochastic Stability of Deep Markov Models Ján Drgoňa Sayak Mukherjee Jiaxin Zhang Frank Liu M. Halappanavar BDL 25 5 0 08 Nov 2021
Neural Flows: Efficient Alternative to Neural ODEs Marin Bilovs Johanna Sommer Syama Sundar Rangapuram Tim Januschowski Stephan Günnemann AI4TS 33 70 0 25 Oct 2021
Deep Learning Approximation of Diffeomorphisms via Linear-Control Systems A. Scagliotti 23 13 0 24 Oct 2021
Conditioning of Random Feature Matrices: Double Descent and Generalization Error Zhijun Chen Hayden Schaeffer 37 12 0 21 Oct 2021
Heavy Ball Neural Ordinary Differential Equations Hedi Xia Vai Suliafu H. Ji T. Nguyen Andrea L. Bertozzi Stanley J. Osher Bao Wang 38 56 0 10 Oct 2021
slimTrain -- A Stochastic Approximation Method for Training Separable Deep Neural Networks Elizabeth Newman Julianne Chung Matthias Chung Lars Ruthotto 47 6 0 28 Sep 2021
Locally-symplectic neural networks for learning volume-preserving dynamics J. Bajārs 34 9 0 19 Sep 2021
On the regularized risk of distributionally robust learning over deep neural networks Camilo A. Garcia Trillos Nicolas García Trillos OOD 45 10 0 13 Sep 2021
Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations Ido Ben-Yair Gil Ben Shalom Moshe Eliasof Eran Treister MQ 36 5 0 31 Aug 2021
Designing Rotationally Invariant Neural Networks from PDEs and Variational Methods Tobias Alt Karl Schrader Joachim Weickert Pascal Peter M. Augustin 22 4 0 31 Aug 2021
Neural Operator: Learning Maps Between Function Spaces Nikola B. Kovachki Zong-Yi Li Burigede Liu Kamyar Azizzadenesheli K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 52 441 0 19 Aug 2021
m-RevNet: Deep Reversible Neural Networks with Momentum Duo Li Shangqi Gao 36 5 0 12 Aug 2021
Training of deep residual networks with stochastic MG/OPT Cyrill Planta Alena Kopanicáková Rolf Krause 32 3 0 09 Aug 2021
PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations Moshe Eliasof E. Haber Eran Treister GNN AI4CE 39 123 0 04 Aug 2021
Machine learning structure preserving brackets for forecasting irreversible processes Kookjin Lee Nathaniel Trask P. Stinis AI4CE 44 43 0 23 Jun 2021
Residual Networks as Flows of Velocity Fields for Diffeomorphic Time Series Alignment Hao Huang Boulbaba Ben Amor Xichan Lin Fan Zhu Yi Fang AI4TS MedIm 22 6 0 22 Jun 2021
Variational multiple shooting for Bayesian ODEs with Gaussian processes Pashupati Hegde Çağatay Yıldız Harri Lähdesmäki Samuel Kaski Markus Heinonen 30 16 0 21 Jun 2021
Stateful ODE-Nets using Basis Function Expansions A. Queiruga N. Benjamin Erichson Liam Hodgkinson Michael W. Mahoney 27 16 0 21 Jun 2021
RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks L. Kozachkov Michaela Ennis Jean-Jacques E. Slotine 22 18 0 16 Jun 2021
Scaling Properties of Deep Residual Networks A. Cohen R. Cont Alain Rossier Renyuan Xu 25 18 0 25 May 2021
Activation function design for deep networks: linearity and effective initialisation Michael Murray V. Abrol Jared Tanner ODL LLMSV 29 18 0 17 May 2021
A unified framework for Hamiltonian deep neural networks C. Galimberti Liang Xu Giancarlo Ferrari-Trecate 42 5 0 27 Apr 2021
Randomized Algorithms for Scientific Computing (RASC) A. Buluç T. Kolda Stefan M. Wild M. Anitescu Anthony Degennaro ... D. Vrabie B. Wohlberg Stephen J. Wright Chao Yang Peter Zwart AI4CE 43 10 0 19 Apr 2021
Almost Surely Stable Deep Dynamics Nathan P. Lawrence Philip D. Loewen M. Forbes Johan U. Backstrom R. Bhushan Gopaluni BDL 40 20 0 26 Mar 2021
JFB: Jacobian-Free Backpropagation for Implicit Networks Samy Wu Fung Howard Heaton Qiuwei Li Daniel McKenzie Stanley Osher W. Yin FedML 35 84 0 23 Mar 2021
Continuous normalizing flows on manifolds Luca Falorsi BDL AI4CE 30 10 0 14 Mar 2021
Learning Contact Dynamics using Physically Structured Neural Networks Andreas Hochlehnert Alexander Terenin Steindór Sæmundsson M. Deisenroth 19 16 0 22 Feb 2021
Deep Equilibrium Architectures for Inverse Problems in Imaging Davis Gilton Greg Ongie Rebecca Willett 49 181 0 16 Feb 2021
Momentum Residual Neural Networks Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 27 57 0 15 Feb 2021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations Winnie Xu Ricky T. Q. Chen Xuechen Li David Duvenaud BDL UQCV 27 46 0 12 Feb 2021
MALI: A memory efficient and reverse accurate integrator for Neural ODEs Juntang Zhuang Nicha Dvornek S. Tatikonda James S. Duncan 27 49 0 09 Feb 2021
Implicit Feature Pyramid Network for Object Detection Tiancai Wang Xinming Zhang Jian Sun ObjD 13 27 0 25 Dec 2020
Physical deep learning based on optimal control of dynamical systems Genki Furuhata T. Niiyama S. Sunada PINN AI4CE 29 14 0 16 Dec 2020
Physics-Informed Neural State Space Models via Learning and Evolution Elliott Skomski Ján Drgoňa Aaron Tuor PINN AI4CE 27 9 0 26 Nov 2020
Dissipative Deep Neural Dynamical Systems Ján Drgoňa Soumya Vasisht Aaron Tuor D. Vrabie 21 7 0 26 Nov 2020
A non-autonomous equation discovery method for time signal classification Ryeongkyung Yoon Harish S. Bhat Braxton Osting 25 2 0 22 Nov 2020
Deep Neural Networks using a Single Neuron: Folded-in-Time Architecture using Feedback-Modulated Delay Loops Florian Stelzer André Röhm Raul Vicente Ingo Fischer University of Tartu AI4CE 19 46 0 19 Nov 2020
Physics-constrained Deep Learning of Multi-zone Building Thermal Dynamics Ján Drgoňa Aaron Tuor V. Chandan D. Vrabie AI4CE 27 115 0 11 Nov 2020
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated Gradients Yifei Huang Yaodong Yu Hongyang R. Zhang Yi Ma Yuan Yao AAML 37 26 0 28 Sep 2020
A Differential Game Theoretic Neural Optimizer for Training Residual Networks Guan-Horng Liu T. Chen Evangelos A. Theodorou 24 2 0 17 Jul 2020