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Neural Tangent Kernel: Convergence and Generalization in Neural Networks

20 June 2018

Papers citing "Neural Tangent Kernel: Convergence and Generalization in Neural Networks"

50 / 1,193 papers shown

Title
LENSLLM: Unveiling Fine-Tuning Dynamics for LLM Selection Xinyue Zeng Haohui Wang Junhong Lin Jun Wu Tyler Cody Dawei Zhou 431 0 0 01 May 2025
On the Importance of Gaussianizing Representations Daniel Eftekhari Vardan Papyan 77 0 0 01 May 2025
Neuronal correlations shape the scaling behavior of memory capacity and nonlinear computational capability of recurrent neural networks Shotaro Takasu Toshio Aoyagi 107 0 0 28 Apr 2025
Reliable and Efficient Inverse Analysis using Physics-Informed Neural Networks with Distance Functions and Adaptive Weight Tuning Shota Deguchi Mitsuteru Asai PINN AI4CE 174 0 0 25 Apr 2025
Deep learning with missing data Tianyi Ma Tengyao Wang R. Samworth 269 1 0 21 Apr 2025
Hadamard product in deep learning: Introduction, Advances and Challenges Grigorios G. Chrysos Yongtao Wu Razvan Pascanu Philip Torr Volkan Cevher AAML 170 2 0 17 Apr 2025
Generalization through variance: how noise shapes inductive biases in diffusion models John J. Vastola DiffM 486 5 0 16 Apr 2025
When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers Hongkang Li Yihua Zhang Shuai Zhang Ming Wang Sijia Liu Pin-Yu Chen MoMe 258 10 0 15 Apr 2025
Divergence of Empirical Neural Tangent Kernel in Classification Problems Zixiong Yu Songtao Tian Guhan Chen 68 0 0 15 Apr 2025
Free Random Projection for In-Context Reinforcement Learning Tomohiro Hayase B. Collins Nakamasa Inoue 91 0 0 09 Apr 2025
PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity Mustafa Burak Gurbuz Xingyu Zheng C. Dovrolis OOD 94 0 0 07 Apr 2025
ReLU Networks as Random Functions: Their Distribution in Probability Space Shreyas Chaudhari J. M. F. Moura 87 0 0 28 Mar 2025
On the Cone Effect in the Learning Dynamics Zhanpeng Zhou Yongyi Yang Jie Ren Mahito Sugiyama Junchi Yan 116 0 0 20 Mar 2025
Neural Tangent Kernel of Neural Networks with Loss Informed by Differential Operators Weiye Gan Yicheng Li Q. Lin Zuoqiang Shi 75 0 0 14 Mar 2025
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model Moritz A. Zanger Pascal R. van der Vaart Wendelin Bohmer M. Spaan UQCV BDL 507 2 0 14 Mar 2025
Learning richness modulates equality reasoning in neural networks William L. Tong Cengiz Pehlevan 66 0 0 12 Mar 2025
Context-aware Biases for Length Extrapolation Ali Veisi Hamidreza Amirzadeh Amir Mansourian 165 1 0 11 Mar 2025
PIED: Physics-Informed Experimental Design for Inverse Problems Apivich Hemachandra Gregory Kang Ruey Lau Szu Hui Ng Bryan Kian Hsiang Low PINN 108 0 0 10 Mar 2025
Make Haste Slowly: A Theory of Emergent Structured Mixed Selectivity in Feature Learning ReLU Networks Devon Jarvis Richard Klein Benjamin Rosman Andrew M. Saxe MLT 148 2 0 08 Mar 2025
Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure Samet Demir Zafer Dogan MLT 94 0 0 02 Mar 2025
Position: Solve Layerwise Linear Models First to Understand Neural Dynamical Phenomena (Neural Collapse, Emergence, Lazy/Rich Regime, and Grokking) Yoonsoo Nam Seok Hyeong Lee Clementine Domine Yea Chan Park Charles London Wonyl Choi Niclas Goring Seungjai Lee AI4CE 209 1 0 28 Feb 2025
Variation Matters: from Mitigating to Embracing Zero-Shot NAS Ranking Function Variation Pavel Rumiantsev Mark Coates 96 0 0 27 Feb 2025
Training Large Neural Networks With Low-Dimensional Error Feedback Maher Hanut Jonathan Kadmon 133 1 0 27 Feb 2025
Bridging Critical Gaps in Convergent Learning: How Representational Alignment Evolves Across Layers, Training, and Distribution Shifts Chaitanya Kapoor Sudhanshu Srivastava Meenakshi Khosla 116 0 0 26 Feb 2025
Convergence of Shallow ReLU Networks on Weakly Interacting Data Léo Dana Francis R. Bach Loucas Pillaud-Vivien MLT 95 2 0 24 Feb 2025
FACTR: Force-Attending Curriculum Training for Contact-Rich Policy Learning Jason Jingzhou Liu Yulong Li Kenneth Shaw Tony Tao Ruslan Salakhutdinov Deepak Pathak OffRL 159 2 0 24 Feb 2025
Feature maps for the Laplacian kernel and its generalizations Sudhendu Ahir Parthe Pandit 101 0 0 24 Feb 2025
Explainable Neural Networks with Guarantees: A Sparse Estimation Approach Antoine Ledent Peng Liu FAtt 355 0 0 20 Feb 2025
Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits Kaining Zhang Liu Liu Min-hsiu Hsieh Dacheng Tao 147 63 0 20 Feb 2025
Linear Mode Connectivity in Differentiable Tree Ensembles Ryuichi Kanoh M. Sugiyama 228 1 0 17 Feb 2025
EquiTabPFN: A Target-Permutation Equivariant Prior Fitted Networks Michael Arbel David Salinas Frank Hutter 133 3 0 10 Feb 2025
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer Blake Bordelon Cengiz Pehlevan AI4CE 241 1 0 04 Feb 2025
Observation Noise and Initialization in Wide Neural Networks Sergio Calvo-Ordoñez Jonathan Plenk Richard Bergna Alvaro Cartea Jose Miguel Hernandez-Lobato Konstantina Palla Kamil Ciosek 116 1 0 03 Feb 2025
STAF: Sinusoidal Trainable Activation Functions for Implicit Neural Representation Alireza Morsali MohammadJavad Vaez Mohammadhossein Soltani Amirhossein Kazerouni Babak Taati Morteza Mohammad-Noori 456 1 0 02 Feb 2025
GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture Md Atik Ahamed Andrew Cheng Qiang Ye Q. Cheng GNN 107 0 0 01 Feb 2025
Position: Curvature Matrices Should Be Democratized via Linear Operators Felix Dangel Runa Eschenhagen Weronika Ormaniec Andres Fernandez Lukas Tatzel Agustinus Kristiadi 135 4 0 31 Jan 2025
Algebra Unveils Deep Learning -- An Invitation to Neuroalgebraic Geometry Giovanni Luca Marchetti Vahid Shahverdi Stefano Mereta Matthew Trager Kathlén Kohn 153 2 0 31 Jan 2025
A theoretical framework for overfitting in energy-based modeling Giovanni Catania A. Decelle Cyril Furtlehner Beatriz Seoane 179 2 0 31 Jan 2025
Scanning Trojaned Models Using Out-of-Distribution Samples Hossein Mirzaei Ali Ansari Bahar Dibaei Nia Mojtaba Nafez Moein Madadi ... Kian Shamsaie Mahdi Hajialilue Jafar Habibi Mohammad Sabokrou M. Rohban OODD 143 3 0 28 Jan 2025
Task Arithmetic in Trust Region: A Training-Free Model Merging Approach to Navigate Knowledge Conflicts Wenju Sun Qingyong Li Wen Wang Yangli-ao Geng Boyang Li 192 5 0 28 Jan 2025
Decentralized Low-Rank Fine-Tuning of Large Language Models Sajjad Ghiasvand Mahnoosh Alizadeh Ramtin Pedarsani ALM 152 2 0 26 Jan 2025
On Learning Representations for Tabular Data Distillation Inwon Kang Parikshit Ram Yi Zhou Horst Samulowitz Oshani Seneviratne DD 113 0 0 23 Jan 2025
Physics of Skill Learning Ziming Liu Yizhou Liu Eric J. Michaud Jeff Gore Max Tegmark 119 2 0 21 Jan 2025
Generating visual explanations from deep networks using implicit neural representations Michal Byra Henrik Skibbe GAN FAtt 111 0 0 20 Jan 2025
Issues with Neural Tangent Kernel Approach to Neural Networks Haoran Liu Anthony S. Tai David J. Crandall Chunfeng Huang 105 0 0 19 Jan 2025
Flexible task abstractions emerge in linear networks with fast and bounded units Kai Sandbrink Jan P. Bauer A. Proca Andrew M. Saxe Christopher Summerfield Ali Hummos 121 2 0 17 Jan 2025
Globally Convergent Variational Inference Declan McNamara J. Loper Jeffrey Regier 101 0 0 14 Jan 2025
Geometry and Optimization of Shallow Polynomial Networks Yossi Arjevani Joan Bruna Joe Kileel Elzbieta Polak Matthew Trager 86 3 0 10 Jan 2025
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input Ziang Chen Rong Ge MLT 150 1 0 10 Jan 2025
Time Transfer: On Optimal Learning Rate and Batch Size In The Infinite Data Limit Oleg Filatov Jan Ebert Jiangtao Wang Stefan Kesselheim 115 4 0 10 Jan 2025