Enhanced Convolutional Neural Tangent Kernels

3 November 2019

Dingli Yu

Papers citing "Enhanced Convolutional Neural Tangent Kernels"

35 / 35 papers shown

Title
Equivariant Neural Tangent Kernels Philipp Misof Pan Kessel Jan E. Gerken 64 0 0 10 Jun 2024
Symmetries in Overparametrized Neural Networks: A Mean-Field View Javier Maass Martínez Joaquin Fontbona FedML MLT 55 2 0 30 May 2024
Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning Yuxiao Wen Arthur Jacot 68 6 0 12 Feb 2024
A Simple Algorithm For Scaling Up Kernel Methods Tengyu Xu Bryan Kelly Semyon Malamud 30 0 0 26 Jan 2023
Global Convergence of SGD On Two Layer Neural Nets Pulkit Gopalani Anirbit Mukherjee 31 5 0 20 Oct 2022
Minimalistic Unsupervised Learning with the Sparse Manifold Transform Yubei Chen Zeyu Yun Yi Ma Bruno A. Olshausen Yann LeCun 54 8 0 30 Sep 2022
Provable Acceleration of Nesterov's Accelerated Gradient Method over Heavy Ball Method in Training Over-Parameterized Neural Networks Xin Liu Wei Tao Wei Li Dazhi Zhan Jun Wang Zhisong Pan ODL 32 1 0 08 Aug 2022
Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels Mohamad Amin Mohamadi Wonho Bae Danica J. Sutherland 35 20 0 25 Jun 2022
TKIL: Tangent Kernel Approach for Class Balanced Incremental Learning Jinlin Xiang Eli Shlizerman CLL 19 8 0 17 Jun 2022
Overcoming the Spectral Bias of Neural Value Approximation Ge Yang Anurag Ajay Pulkit Agrawal 36 25 0 09 Jun 2022
Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality Chandrashekar Lakshminarayanan Ashutosh Kumar Singh A. Rajkumar AI4CE 31 1 0 01 Mar 2022
Sample Efficiency of Data Augmentation Consistency Regularization Shuo Yang Yijun Dong Rachel A. Ward Inderjit S. Dhillon Sujay Sanghavi Qi Lei AAML 31 17 0 24 Feb 2022
Largest Eigenvalues of the Conjugate Kernel of Single-Layered Neural Networks L. Benigni Sandrine Péché 42 8 0 13 Jan 2022
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime Rui Zhang Shihua Zhang TDI 32 21 0 15 Dec 2021
Learning with convolution and pooling operations in kernel methods Theodor Misiakiewicz Song Mei MLT 15 29 0 16 Nov 2021
Quantum tangent kernel Norihito Shirai K. Kubo K. Mitarai Keisuke Fujii 38 27 0 04 Nov 2021
Quantifying Epistemic Uncertainty in Deep Learning Ziyi Huang Henry Lam Haofeng Zhang UQCV BDL UD PER 24 12 0 23 Oct 2021
Deep Networks Provably Classify Data on Curves Tingran Wang Sam Buchanan D. Gilboa John N. Wright 25 9 0 29 Jul 2021
Dataset Distillation with Infinitely Wide Convolutional Networks Timothy Nguyen Roman Novak Lechao Xiao Jaehoon Lee DD 51 231 0 27 Jul 2021
Generalization Guarantees for Neural Architecture Search with Train-Validation Split Samet Oymak Mingchen Li Mahdi Soltanolkotabi AI4CE OOD 41 13 0 29 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
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 55 89 0 25 Feb 2021
A Convergence Theory Towards Practical Over-parameterized Deep Neural Networks Asaf Noy Yi Tian Xu Y. Aflalo Lihi Zelnik-Manor Rong Jin 41 3 0 12 Jan 2021
Mixed-Privacy Forgetting in Deep Networks Aditya Golatkar Alessandro Achille Avinash Ravichandran M. Polito Stefano Soatto CLL MU 130 161 0 24 Dec 2020
Power of data in quantum machine learning Hsin-Yuan Huang Michael Broughton Masoud Mohseni Ryan Babbush Sergio Boixo Hartmut Neven Jarrod R. McClean 25 624 0 03 Nov 2020
On the Similarity between the Laplace and Neural Tangent Kernels Amnon Geifman A. Yadav Yoni Kasten Meirav Galun David Jacobs Ronen Basri 23 89 0 03 Jul 2020
A Revision of Neural Tangent Kernel-based Approaches for Neural Networks Kyungsu Kim A. Lozano Eunho Yang AAML 40 0 0 02 Jul 2020
Kernel Alignment Risk Estimator: Risk Prediction from Training Data Arthur Jacot Berfin cSimcsek Francesco Spadaro Clément Hongler Franck Gabriel 22 67 0 17 Jun 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 26 60 0 17 May 2020
Modularizing Deep Learning via Pairwise Learning With Kernels Shiyu Duan Shujian Yu José C. Príncipe MoMe 27 20 0 12 May 2020
Provable Training of a ReLU Gate with an Iterative Non-Gradient Algorithm Sayar Karmakar Anirbit Mukherjee 14 7 0 08 May 2020
On Infinite-Width Hypernetworks Etai Littwin Tomer Galanti Lior Wolf Greg Yang 14 11 0 27 Mar 2020
Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations Aditya Golatkar Alessandro Achille Stefano Soatto MU OOD 27 189 0 05 Mar 2020
Optimization for deep learning: theory and algorithms Ruoyu Sun ODL 27 168 0 19 Dec 2019
Why bigger is not always better: on finite and infinite neural networks Laurence Aitchison 175 51 0 17 Oct 2019