Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent

18 February 2019

Jascha Narain Sohl-Dickstein

Jeffrey Pennington

ArXiv PDF HTML

Papers citing "Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent"

50 / 288 papers shown

Title
Convergence of Invariant Graph Networks Chen Cai Yusu Wang 63 4 0 25 Jan 2022
Deep Q-learning: a robust control approach B. Varga Balázs Kulcsár M. Chehreghani OOD 30 9 0 21 Jan 2022
Overview frequency principle/spectral bias in deep learning Z. Xu Yaoyu Zhang Tao Luo FaML 33 66 0 19 Jan 2022
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks Benjamin Bowman Guido Montúfar 28 11 0 12 Jan 2022
Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs Inbar Seroussi Gadi Naveh Zohar Ringel 35 51 0 31 Dec 2021
GPEX, A Framework For Interpreting Artificial Neural Networks Amir Akbarnejad G. Bigras Nilanjan Ray 47 4 0 18 Dec 2021
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime Rui Zhang Shihua Zhang TDI 27 21 0 15 Dec 2021
Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time Zhao Song Licheng Zhang Ruizhe Zhang 32 64 0 14 Dec 2021
Learning Curves for Continual Learning in Neural Networks: Self-Knowledge Transfer and Forgetting Ryo Karakida S. Akaho CLL 32 11 0 03 Dec 2021
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models Tri Dao Beidi Chen Kaizhao Liang Jiaming Yang Zhao Song Atri Rudra Christopher Ré 33 75 0 30 Nov 2021
On the Equivalence between Neural Network and Support Vector Machine Yilan Chen Wei Huang Lam M. Nguyen Tsui-Wei Weng AAML 25 18 0 11 Nov 2021
Neural Networks as Kernel Learners: The Silent Alignment Effect Alexander B. Atanasov Blake Bordelon Cengiz Pehlevan MLT 26 75 0 29 Oct 2021
Quantifying Epistemic Uncertainty in Deep Learning Ziyi Huang H. Lam Haofeng Zhang UQCV BDL UD PER 24 12 0 23 Oct 2021
Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded learning Soufiane Hayou Bo He Gintare Karolina Dziugaite 37 2 0 22 Oct 2021
Deep Active Learning by Leveraging Training Dynamics Haonan Wang Wei Huang Ziwei Wu A. Margenot Hanghang Tong Jingrui He AI4CE 27 33 0 16 Oct 2021
AIR-Net: Adaptive and Implicit Regularization Neural Network for Matrix Completion Zhemin Li Tao Sun Hongxia Wang Bao Wang 50 6 0 12 Oct 2021
New Insights into Graph Convolutional Networks using Neural Tangent Kernels Mahalakshmi Sabanayagam P. Esser D. Ghoshdastidar 26 6 0 08 Oct 2021
Improved architectures and training algorithms for deep operator networks Sizhuang He Hanwen Wang P. Perdikaris AI4CE 52 105 0 04 Oct 2021
Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments Viktor Zaverkin David Holzmüller Ingo Steinwart Johannes Kastner 29 19 0 20 Sep 2021
NASI: Label- and Data-agnostic Neural Architecture Search at Initialization Yao Shu Shaofeng Cai Zhongxiang Dai Beng Chin Ooi K. H. Low 24 43 0 02 Sep 2021
On Accelerating Distributed Convex Optimizations Kushal Chakrabarti Nirupam Gupta Nikhil Chopra 29 7 0 19 Aug 2021
Dataset Distillation with Infinitely Wide Convolutional Networks Timothy Nguyen Roman Novak Lechao Xiao Jaehoon Lee DD 51 231 0 27 Jul 2021
The Limiting Dynamics of SGD: Modified Loss, Phase Space Oscillations, and Anomalous Diffusion D. Kunin Javier Sagastuy-Breña Lauren Gillespie Eshed Margalit Hidenori Tanaka Surya Ganguli Daniel L. K. Yamins 31 15 0 19 Jul 2021
Rethinking Positional Encoding Jianqiao Zheng Sameera Ramasinghe Simon Lucey 27 51 0 06 Jul 2021
The Values Encoded in Machine Learning Research Abeba Birhane Pratyusha Kalluri Dallas Card William Agnew Ravit Dotan Michelle Bao 41 274 0 29 Jun 2021
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation Haoxiang Wang Han Zhao Bo-wen Li 37 88 0 16 Jun 2021
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios Alessandro Favero Francesco Cagnetta M. Wyart 30 31 0 16 Jun 2021
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective Akhilan Boopathy Ila Fiete 41 9 0 15 Jun 2021
What can linearized neural networks actually say about generalization? Guillermo Ortiz-Jiménez Seyed-Mohsen Moosavi-Dezfooli P. Frossard 29 43 0 12 Jun 2021
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective Geoff Pleiss John P. Cunningham 28 24 0 11 Jun 2021
A Neural Tangent Kernel Perspective of GANs Jean-Yves Franceschi Emmanuel de Bézenac Ibrahim Ayed Mickaël Chen Sylvain Lamprier Patrick Gallinari 37 26 0 10 Jun 2021
A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs Gadi Naveh Zohar Ringel SSL MLT 36 31 0 08 Jun 2021
The Future is Log-Gaussian: ResNets and Their Infinite-Depth-and-Width Limit at Initialization Mufan Li Mihai Nica Daniel M. Roy 32 33 0 07 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 31 124 0 14 May 2021
Global Convergence of Three-layer Neural Networks in the Mean Field Regime H. Pham Phan-Minh Nguyen MLT AI4CE 41 19 0 11 May 2021
Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes James Lucas Juhan Bae Michael Ruogu Zhang Stanislav Fort R. Zemel Roger C. Grosse MoMe 164 28 0 22 Apr 2021
Unsupervised Shape Completion via Deep Prior in the Neural Tangent Kernel Perspective Lei Chu Hao Pan Wenping Wang 3DPC 34 11 0 19 Apr 2021
Fast Adaptation with Linearized Neural Networks Wesley J. Maddox Shuai Tang Pablo G. Moreno A. Wilson Andreas C. Damianou 32 32 0 02 Mar 2021
Computing the Information Content of Trained Neural Networks Jeremy Bernstein Yisong Yue 27 4 0 01 Mar 2021
Experiments with Rich Regime Training for Deep Learning Xinyan Li A. Banerjee 32 2 0 26 Feb 2021
Provable Super-Convergence with a Large Cyclical Learning Rate Samet Oymak 35 12 0 22 Feb 2021
Explaining Neural Scaling Laws Yasaman Bahri Ethan Dyer Jared Kaplan Jaehoon Lee Utkarsh Sharma 27 250 0 12 Feb 2021
A linearized framework and a new benchmark for model selection for fine-tuning Aditya Deshpande Alessandro Achille Avinash Ravichandran Hao Li L. Zancato Charless C. Fowlkes Rahul Bhotika Stefano Soatto Pietro Perona ALM 118 46 0 29 Jan 2021
Estimating informativeness of samples with Smooth Unique Information Hrayr Harutyunyan Alessandro Achille Giovanni Paolini Orchid Majumder Avinash Ravichandran Rahul Bhotika Stefano Soatto 27 24 0 17 Jan 2021
Reproducing Activation Function for Deep Learning Senwei Liang Liyao Lyu Chunmei Wang Haizhao Yang 36 21 0 13 Jan 2021
LQF: Linear Quadratic Fine-Tuning Alessandro Achille Aditya Golatkar Avinash Ravichandran M. Polito Stefano Soatto 29 27 0 21 Dec 2020
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sizhuang He Hanwen Wang P. Perdikaris 131 441 0 18 Dec 2020
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics D. Kunin Javier Sagastuy-Breña Surya Ganguli Daniel L. K. Yamins Hidenori Tanaka 107 77 0 08 Dec 2020
Faster Non-Convex Federated Learning via Global and Local Momentum Rudrajit Das Anish Acharya Abolfazl Hashemi Sujay Sanghavi Inderjit S. Dhillon Ufuk Topcu FedML 40 82 0 07 Dec 2020
Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent Kangqiao Liu Liu Ziyin Masakuni Ueda MLT 61 37 0 07 Dec 2020