On Exact Computation with an Infinitely Wide Neural Net

26 April 2019

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

50 / 266 papers shown

Title
Overcoming the Spectral Bias of Neural Value Approximation Ge Yang Anurag Ajay Pulkit Agrawal 34 25 0 09 Jun 2022
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials Eshaan Nichani Yunzhi Bai Jason D. Lee 29 10 0 08 Jun 2022
Infinite Recommendation Networks: A Data-Centric Approach Noveen Sachdeva Mehak Preet Dhaliwal Carole-Jean Wu Julian McAuley DD 39 28 0 03 Jun 2022
Dual Convexified Convolutional Neural Networks Site Bai Chuyang Ke Jean Honorio 24 1 0 27 May 2022
Global Convergence of Over-parameterized Deep Equilibrium Models Zenan Ling Xingyu Xie Qiuhao Wang Zongpeng Zhang Zhouchen Lin 34 12 0 27 May 2022
Analyzing Tree Architectures in Ensembles via Neural Tangent Kernel Ryuichi Kanoh M. Sugiyama 31 2 0 25 May 2022
Empirical Phase Diagram for Three-layer Neural Networks with Infinite Width Hanxu Zhou Qixuan Zhou Zhenyuan Jin Yaoyu Zhang Tao Luo Zhi-Qin John Xu 25 21 0 24 May 2022
Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture Libin Zhu Chaoyue Liu M. Belkin GNN AI4CE 23 4 0 24 May 2022
Gaussian Pre-Activations in Neural Networks: Myth or Reality? Pierre Wolinski Julyan Arbel AI4CE 76 8 0 24 May 2022
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks Blake Bordelon Cengiz Pehlevan MLT 42 77 0 19 May 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation Jimmy Ba Murat A. Erdogdu Taiji Suzuki Zhichao Wang Denny Wu Greg Yang MLT 42 121 0 03 May 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng Jiaxin Shi Jun Zhu 29 18 0 30 Apr 2022
Wide and Deep Neural Networks Achieve Optimality for Classification Adityanarayanan Radhakrishnan M. Belkin Caroline Uhler 27 18 0 29 Apr 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 33 68 0 16 Apr 2022
Machine Learning and Deep Learning -- A review for Ecologists Maximilian Pichler F. Hartig 47 127 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 33 27 0 17 Mar 2022
Generalization Through The Lens Of Leave-One-Out Error Gregor Bachmann Thomas Hofmann Aurelien Lucchi 67 7 0 07 Mar 2022
Better Supervisory Signals by Observing Learning Paths Yi Ren Shangmin Guo Danica J. Sutherland 33 21 0 04 Mar 2022
Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality Chandrashekar Lakshminarayanan Ashutosh Kumar Singh A. Rajkumar AI4CE 28 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 Barnett 27 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 31 1 0 14 Feb 2022
A Geometric Understanding of Natural Gradient Qinxun Bai S. Rosenberg Wei Xu 23 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 Arthur Gretton Jennifer Dy 31 3 0 01 Feb 2022
Interplay between depth of neural networks and locality of target functions Takashi Mori Masakuni Ueda 25 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 Zohar Ringel 37 51 0 31 Dec 2021
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime Rui Zhang Shihua Zhang TDI 29 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 50 1 0 07 Dec 2021
Fast Graph Neural Tangent Kernel via Kronecker Sketching Shunhua Jiang Yunze Man Zhao 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 33 87 0 03 Dec 2021
Forward Operator Estimation in Generative Models with Kernel Transfer Operators Z. Huang Rudrasis Chakraborty Vikas Singh GAN 16 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 Song Atri Rudra Christopher Ré 33 75 0 30 Nov 2021
Embedding Principle: a hierarchical structure of loss landscape of deep neural networks Tao Luo Yuqing Li Zhongwang Zhang Yaoyu Zhang Z. Xu 29 22 0 30 Nov 2021
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization Thanh Nguyen-Tang Sunil R. Gupta A. Nguyen Svetha Venkatesh OffRL 31 29 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 25 18 0 11 Nov 2021
Empirical analysis of representation learning and exploration in neural kernel bandits Michal Lisicki Arash Afkanpour Graham W. Taylor 18 0 0 05 Nov 2021
A Johnson--Lindenstrauss Framework for Randomly Initialized CNNs Ido Nachum Jan Hkazla Michael C. Gastpar Anatoly Khina 36 0 0 03 Nov 2021
Neural Networks as Kernel Learners: The Silent Alignment Effect Alexander B. Atanasov Blake Bordelon Cengiz Pehlevan MLT 28 75 0 29 Oct 2021
Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives Zida Cheng Chuanwei Ruan Siheng Chen Sushant Kumar Ya Zhang 27 16 0 23 Oct 2021
Quantifying Epistemic Uncertainty in Deep Learning Ziyi Huang Henry Lam Haofeng Zhang UQCV BDL UD PER 24 12 0 23 Oct 2021
Deep Active Learning by Leveraging Training Dynamics Haonan Wang Wei Huang Ziwei Wu A. Margenot Hanghang Tong Jingrui He AI4CE 29 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
A global convergence theory for deep ReLU implicit networks via over-parameterization Tianxiang Gao Hailiang Liu Jia Liu Hridesh Rajan Hongyang Gao MLT 36 16 0 11 Oct 2021
Does Preprocessing Help Training Over-parameterized Neural Networks? Zhao Song Shuo Yang Ruizhe Zhang 38 49 0 09 Oct 2021
New Insights into Graph Convolutional Networks using Neural Tangent Kernels Mahalakshmi Sabanayagam P. Esser D. Ghoshdastidar 29 6 0 08 Oct 2021