Neural Tangents: Fast and Easy Infinite Neural Networks in Python

5 December 2019

Jascha Narain Sohl-Dickstein

S. Schoenholz

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Papers citing "Neural Tangents: Fast and Easy Infinite Neural Networks in Python"

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Title
Generalized Kernel Inducing Points by Duality Gap for Dataset Distillation Tatsuya Aoyama Hanting Yang Hiroyuki Hanada Satoshi Akahane Tomonari Tanaka ... Noriaki Hashimoto Taro Murayama Hanju Lee Shinya Kojima Ichiro Takeuchi 72 0 0 18 Feb 2025
STAF: Sinusoidal Trainable Activation Functions for Implicit Neural Representation Alireza Morsali MohammadJavad Vaez Hossein Soltani A. Kazerouni Babak Taati Morteza Mohammad-Noori 156 1 0 02 Feb 2025
Fast Training of Sinusoidal Neural Fields via Scaling Initialization Taesun Yeom Sangyoon Lee Jaeho Lee 61 2 0 07 Oct 2024
Equivariant Neural Tangent Kernels Philipp Misof Pan Kessel Jan E. Gerken 64 0 0 10 Jun 2024
Connecting NTK and NNGP: A Unified Theoretical Framework for Wide Neural Network Learning Dynamics Yehonatan Avidan Qianyi Li H. Sompolinsky 60 8 0 08 Sep 2023
Training-Free Neural Active Learning with Initialization-Robustness Guarantees Apivich Hemachandra Zhongxiang Dai Jasraj Singh See-Kiong Ng K. H. Low AAML 36 6 0 07 Jun 2023
Learning ground states of gapped quantum Hamiltonians with Kernel Methods Clemens Giuliani F. Vicentini R. Rossi Giuseppe Carleo 19 7 0 15 Mar 2023
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation Noel Loo Ramin Hasani Mathias Lechner Alexander Amini Daniela Rus DD 42 5 0 02 Feb 2023
A Simple Algorithm For Scaling Up Kernel Methods Tengyu Xu Bryan Kelly Semyon Malamud 16 0 0 26 Jan 2023
Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data Zongyu Dai Zhiqi Bu Q. Long 35 4 0 23 Nov 2022
Proximal Mean Field Learning in Shallow Neural Networks Alexis M. H. Teter Iman Nodozi A. Halder FedML 43 1 0 25 Oct 2022
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo Ramin Hasani Alexander Amini Daniela Rus AAML 34 13 0 21 Oct 2022
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? Nikolaos Tsilivis Julia Kempe AAML 47 17 0 11 Oct 2022
Second-order regression models exhibit progressive sharpening to the edge of stability Atish Agarwala Fabian Pedregosa Jeffrey Pennington 35 26 0 10 Oct 2022
Joint Embedding Self-Supervised Learning in the Kernel Regime B. Kiani Randall Balestriero Yubei Chen S. Lloyd Yann LeCun SSL 49 13 0 29 Sep 2022
Variational Inference for Infinitely Deep Neural Networks Achille Nazaret David M. Blei BDL 25 11 0 21 Sep 2022
Can we achieve robustness from data alone? Nikolaos Tsilivis Jingtong Su Julia Kempe OOD DD 36 18 0 24 Jul 2022
Gradient-based Bi-level Optimization for Deep Learning: A Survey Can Chen Xiangshan Chen Chen Ma Zixuan Liu Xue Liu 94 35 0 24 Jul 2022
Graph Neural Network Bandits Parnian Kassraie Andreas Krause Ilija Bogunovic 26 11 0 13 Jul 2022
Memory Safe Computations with XLA Compiler A. Artemev Tilman Roeder Mark van der Wilk 29 8 0 28 Jun 2022
Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels Mohamad Amin Mohamadi Wonho Bae Danica J. Sutherland 30 20 0 25 Jun 2022
Fast Finite Width Neural Tangent Kernel Roman Novak Jascha Narain Sohl-Dickstein S. Schoenholz AAML 22 53 0 17 Jun 2022
Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling Jiri Hron Roman Novak Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 48 6 0 15 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 33 28 0 03 Jun 2022
On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity Vincent Szolnoky Viktor Andersson Balázs Kulcsár Rebecka Jörnsten 42 5 0 25 May 2022
Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel Ziyang Jiang Tongshu Zheng Yiling Liu David Carlson 30 4 0 15 May 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng Jiaxin Shi Jun Zhu 27 18 0 30 Apr 2022
Machine Learning and Deep Learning -- A review for Ecologists Maximilian Pichler F. Hartig 45 127 0 11 Apr 2022
Random matrix analysis of deep neural network weight matrices M. Thamm Max Staats B. Rosenow 35 12 0 28 Mar 2022
Generalization Through The Lens Of Leave-One-Out Error Gregor Bachmann Thomas Hofmann Aurelien Lucchi 55 7 0 07 Mar 2022
Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior Javier Antorán Riccardo Barbano Johannes Leuschner José Miguel Hernández-Lobato Bangti Jin UQCV 30 10 0 28 Feb 2022
Finding Dynamics Preserving Adversarial Winning Tickets Xupeng Shi Pengfei Zheng Adam Ding Yuan Gao Weizhong Zhang AAML 23 1 0 14 Feb 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next S. Cuomo Vincenzo Schiano Di Cola F. Giampaolo G. Rozza Maizar Raissi F. Piccialli PINN 26 1,180 0 14 Jan 2022
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
A Structured Dictionary Perspective on Implicit Neural Representations Gizem Yüce Guillermo Ortiz-Jiménez Beril Besbinar P. Frossard 31 87 0 03 Dec 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
Data Summarization via Bilevel Optimization Zalan Borsos Mojmír Mutný Marco Tagliasacchi Andreas Krause 30 8 0 26 Sep 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
Dataset Distillation with Infinitely Wide Convolutional Networks Timothy Nguyen Roman Novak Lechao Xiao Jaehoon Lee DD 51 229 0 27 Jul 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
What can linearized neural networks actually say about generalization? Guillermo Ortiz-Jiménez Seyed-Mohsen Moosavi-Dezfooli P. Frossard 29 43 0 12 Jun 2021
A Neural Tangent Kernel Perspective of GANs Jean-Yves Franceschi Emmanuel de Bézenac Ibrahim Ayed Mickaël Chen Sylvain Lamprier Patrick Gallinari 34 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
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 31 124 0 14 May 2021
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure Samuel Kim Peter Y. Lu Charlotte Loh Jamie Smith Jasper Snoek M. Soljavcić BDL AI4CE 103 17 0 23 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
Explaining Neural Scaling Laws Yasaman Bahri Ethan Dyer Jared Kaplan Jaehoon Lee Utkarsh Sharma 27 250 0 12 Feb 2021