On Exact Computation with an Infinitely Wide Neural Net

26 April 2019

Papers citing "On Exact Computation with an Infinitely Wide Neural Net"

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Title
Machine Learning and Deep Learning -- A review for Ecologists Maximilian Pichler F. Hartig 42 127 0 11 Apr 2022
On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels Amnon Geifman Meirav Galun David Jacobs Ronen Basri 30 13 0 17 Mar 2022
Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot Learning Haoxiang Wang Yite Wang Ruoyu Sun Bo-wen Li 29 27 0 17 Mar 2022
Generalization Through The Lens Of Leave-One-Out Error Gregor Bachmann Thomas Hofmann Aurelien Lucchi 49 7 0 07 Mar 2022
Better Supervisory Signals by Observing Learning Paths Yi Ren Shangmin Guo Danica J. Sutherland 30 21 0 04 Mar 2022
Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality Chandrashekar Lakshminarayanan Ashutosh Kumar Singh A. Rajkumar AI4CE 18 1 0 01 Mar 2022
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity Shiyun Xu Zhiqi Bu Pratik Chaudhari Ian J. Barnett 19 21 0 25 Feb 2022
Random Feature Amplification: Feature Learning and Generalization in Neural Networks Spencer Frei Niladri S. Chatterji Peter L. Bartlett MLT 30 29 0 15 Feb 2022
Finding Dynamics Preserving Adversarial Winning Tickets Xupeng Shi Pengfei Zheng Adam Ding Yuan Gao Weizhong Zhang AAML 21 1 0 14 Feb 2022
A Geometric Understanding of Natural Gradient Qinxun Bai S. Rosenberg Wei Xu 21 2 0 13 Feb 2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning Wei Huang Chunrui Liu Yilan Chen Tianyu Liu R. Xu BDL MLT 19 2 0 04 Feb 2022
Deep Layer-wise Networks Have Closed-Form Weights Chieh-Tsai Wu A. Masoomi A. Gretton Jennifer Dy 29 3 0 01 Feb 2022
Interplay between depth of neural networks and locality of target functions Takashi Mori Masakuni Ueda 19 0 0 28 Jan 2022
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems Jack Parker-Holder Raghunandan Rajan Xingyou Song André Biedenkapp Yingjie Miao ... Vu-Linh Nguyen Roberto Calandra Aleksandra Faust Frank Hutter Marius Lindauer AI4CE 33 100 0 11 Jan 2022
Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs Inbar Seroussi Gadi Naveh Z. Ringel 30 50 0 31 Dec 2021
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime Rui Zhang Shihua Zhang TDI 19 21 0 15 Dec 2021
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks P. Esser L. C. Vankadara D. Ghoshdastidar 28 53 0 07 Dec 2021
A generalization gap estimation for overparameterized models via the Langevin functional variance Akifumi Okuno Keisuke Yano 38 1 0 07 Dec 2021
Fast Graph Neural Tangent Kernel via Kronecker Sketching Shunhua Jiang Yunze Man Zhao-quan Song Zheng Yu Danyang Zhuo 29 6 0 04 Dec 2021
A Structured Dictionary Perspective on Implicit Neural Representations Gizem Yüce Guillermo Ortiz-Jiménez Beril Besbinar P. Frossard 31 86 0 03 Dec 2021
Forward Operator Estimation in Generative Models with Kernel Transfer Operators Z. Huang Rudrasis Chakraborty Vikas Singh GAN 14 3 0 01 Dec 2021
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models Tri Dao Beidi Chen Kaizhao Liang Jiaming Yang Zhao-quan Song Atri Rudra Christopher Ré 33 75 0 30 Nov 2021
Embedding Principle: a hierarchical structure of loss landscape of deep neural networks Yaoyu Zhang Yuqing Li Zhongwang Zhang Tao Luo Z. Xu 21 21 0 30 Nov 2021
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization Thanh Nguyen-Tang Sunil R. Gupta A. Nguyen Svetha Venkatesh OffRL 24 28 0 27 Nov 2021
Learning with convolution and pooling operations in kernel methods Theodor Misiakiewicz Song Mei MLT 15 29 0 16 Nov 2021
On the Equivalence between Neural Network and Support Vector Machine Yilan Chen Wei Huang Lam M. Nguyen Tsui-Wei Weng AAML 17 18 0 11 Nov 2021
A Johnson--Lindenstrauss Framework for Randomly Initialized CNNs Ido Nachum Jan Hkazla Michael C. Gastpar Anatoly Khina 33 0 0 03 Nov 2021
Neural Networks as Kernel Learners: The Silent Alignment Effect Alexander B. Atanasov Blake Bordelon C. Pehlevan MLT 24 75 0 29 Oct 2021
Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives Zida Cheng Chuanwei Ruan Siheng Chen Sushant Kumar Ya-Qin Zhang 22 16 0 23 Oct 2021
AIR-Net: Adaptive and Implicit Regularization Neural Network for Matrix Completion Zhemin Li Tao Sun Hongxia Wang Bao Wang 42 6 0 12 Oct 2021
A global convergence theory for deep ReLU implicit networks via over-parameterization Tianxiang Gao Hailiang Liu Jia Liu Hridesh Rajan Hongyang Gao MLT 23 16 0 11 Oct 2021
Does Preprocessing Help Training Over-parameterized Neural Networks? Zhao-quan Song Shuo Yang Ruizhe Zhang 35 49 0 09 Oct 2021
New Insights into Graph Convolutional Networks using Neural Tangent Kernels Mahalakshmi Sabanayagam P. Esser D. Ghoshdastidar 21 6 0 08 Oct 2021
EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits Yikun Ban Yuchen Yan A. Banerjee Jingrui He OffRL 29 39 0 07 Oct 2021
On the Global Convergence of Gradient Descent for multi-layer ResNets in the mean-field regime Zhiyan Ding Shi Chen Qin Li S. Wright MLT AI4CE 30 11 0 06 Oct 2021
Exponentially Many Local Minima in Quantum Neural Networks Xuchen You Xiaodi Wu 72 51 0 06 Oct 2021
Data Summarization via Bilevel Optimization Zalan Borsos Mojmír Mutný Marco Tagliasacchi Andreas Krause 30 8 0 26 Sep 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 21 19 0 20 Sep 2021
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization Difan Zou Yuan Cao Yuanzhi Li Quanquan Gu MLT AI4CE 44 38 0 25 Aug 2021
Simple, Fast, and Flexible Framework for Matrix Completion with Infinite Width Neural Networks Adityanarayanan Radhakrishnan George Stefanakis M. Belkin Caroline Uhler 30 25 0 31 Jul 2021
Batch Active Learning at Scale Gui Citovsky Giulia DeSalvo Claudio Gentile Lazaros Karydas Anand Rajagopalan Afshin Rostamizadeh Sanjiv Kumar 15 150 0 29 Jul 2021
Dataset Distillation with Infinitely Wide Convolutional Networks Timothy Nguyen Roman Novak Lechao Xiao Jaehoon Lee DD 35 229 0 27 Jul 2021
The Values Encoded in Machine Learning Research Abeba Birhane Pratyusha Kalluri Dallas Card William Agnew Ravit Dotan Michelle Bao 25 274 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 16 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
Precise characterization of the prior predictive distribution of deep ReLU networks Lorenzo Noci Gregor Bachmann Kevin Roth Sebastian Nowozin Thomas Hofmann BDL UQCV 23 32 0 11 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 31 26 0 10 Jun 2021