Neural Kernels Without Tangents

4 March 2020

Jonathan Ragan-Kelley

Benjamin Recht

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Papers citing "Neural Kernels Without Tangents"

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Title
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos Dayal Singh Kalra Tianyu He M. Barkeshli 54 4 0 17 Feb 2025
A Simple Algorithm For Scaling Up Kernel Methods Tengyu Xu Bryan Kelly Semyon Malamud 16 0 0 26 Jan 2023
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? Nikolaos Tsilivis Julia Kempe AAML 44 17 0 11 Oct 2022
Minimalistic Unsupervised Learning with the Sparse Manifold Transform Yubei Chen Zeyu Yun Y. Ma Bruno A. Olshausen Yann LeCun 52 8 0 30 Sep 2022
Formal Conceptual Views in Neural Networks Johannes Hirth Tom Hanika 17 2 0 27 Sep 2022
Can we achieve robustness from data alone? Nikolaos Tsilivis Jingtong Su Julia Kempe OOD DD 36 18 0 24 Jul 2022
Largest Eigenvalues of the Conjugate Kernel of Single-Layered Neural Networks L. Benigni Sandrine Péché 42 8 0 13 Jan 2022
Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs Inbar Seroussi Gadi Naveh Zohar Ringel 33 50 0 31 Dec 2021
Learning with convolution and pooling operations in kernel methods Theodor Misiakiewicz Song Mei MLT 15 29 0 16 Nov 2021
VC dimension of partially quantized neural networks in the overparametrized regime Yutong Wang Clayton D. Scott 25 1 0 06 Oct 2021
Dataset Distillation with Infinitely Wide Convolutional Networks Timothy Nguyen Roman Novak Lechao Xiao Jaehoon Lee DD 49 229 0 27 Jul 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 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
Generalization Guarantees for Neural Architecture Search with Train-Validation Split Samet Oymak Mingchen Li Mahdi Soltanolkotabi AI4CE OOD 36 13 0 29 Apr 2021
Explaining Neural Scaling Laws Yasaman Bahri Ethan Dyer Jared Kaplan Jaehoon Lee Utkarsh Sharma 27 250 0 12 Feb 2021
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning Zeyuan Allen-Zhu Yuanzhi Li FedML 60 355 0 17 Dec 2020
Dataset Meta-Learning from Kernel Ridge-Regression Timothy Nguyen Zhourung Chen Jaehoon Lee DD 36 238 0 30 Oct 2020
Stable ResNet Soufiane Hayou Eugenio Clerico Bo He George Deligiannidis Arnaud Doucet Judith Rousseau ODL SSeg 46 51 0 24 Oct 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
Modularizing Deep Learning via Pairwise Learning With Kernels Shiyu Duan Shujian Yu José C. Príncipe MoMe 27 20 0 12 May 2020
Convex Geometry and Duality of Over-parameterized Neural Networks Tolga Ergen Mert Pilanci MLT 42 54 0 25 Feb 2020
Self-Distillation Amplifies Regularization in Hilbert Space H. Mobahi Mehrdad Farajtabar Peter L. Bartlett 19 226 0 13 Feb 2020
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 35 191 0 02 Oct 2018