{"total":52,"rows":[{"id":"2102.07033","title":"PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them","created":"2021-02-13","cited_by_count":200,"area":null},{"id":"2111.00034","title":"Neural Networks as Kernel Learners: The Silent Alignment Effect","created":"2021-10-29","cited_by_count":106,"area":null},{"id":"2202.05798","title":"The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns via Spotlights of Attention","created":"2022-02-11","cited_by_count":46,"area":null},{"id":"2109.08063","title":"Associative Memories via Predictive Coding","created":"2021-09-16","cited_by_count":44,"area":null},{"id":"2109.03429","title":"Computing on Functions Using Randomized Vector Representations","created":"2021-09-08","cited_by_count":41,"area":null},{"id":"2301.04011","title":"Learning Support and Trivial Prototypes for Interpretable Image Classification","created":"2023-01-08","cited_by_count":38,"area":null},{"id":"2203.10036","title":"On the Generalization Mystery in Deep Learning","created":"2022-03-18","cited_by_count":25,"area":null},{"id":"2111.06063","title":"On the Equivalence between Neural Network and Support Vector Machine","created":"2021-11-11","cited_by_count":17,"area":null},{"id":"2103.10935","title":"Data-driven geophysical forecasting: Simple, low-cost, and accurate baselines with kernel methods","created":"2021-02-13","cited_by_count":15,"area":null},{"id":"2110.12231","title":"Learning curves for Gaussian process regression with power-law priors and targets","created":"2021-10-23","cited_by_count":15,"area":null},{"id":"2102.03799","title":"Online Limited Memory Neural-Linear Bandits with Likelihood Matching","created":"2021-02-07","cited_by_count":14,"area":null},{"id":"2103.05863","title":"AutoDO: Robust AutoAugment for Biased Data with Label Noise via Scalable Probabilistic Implicit Differentiation","created":"2021-03-10","cited_by_count":14,"area":null},{"id":"2104.09582","title":"Robust Uncertainty Bounds in Reproducing Kernel Hilbert Spaces: A Convex Optimization Approach","created":"2021-04-19","cited_by_count":14,"area":null},{"id":"2210.12030","title":"Evolution of Neural Tangent Kernels under Benign and Adversarial Training","created":"2022-10-21","cited_by_count":14,"area":null},{"id":"2403.18494","title":"Learning in PINNs: Phase transition, diffusion equilibrium, and generalization","created":"2024-03-27","cited_by_count":13,"area":null},{"id":"2502.07998","title":"Adaptive kernel predictors from feature-learning infinite limits of neural networks","created":"2025-02-11","cited_by_count":13,"area":null},{"id":"2202.06438","title":"Learning from Randomly Initialized Neural Network Features","created":"2022-02-13","cited_by_count":12,"area":null},{"id":"2206.06544","title":"A Survey of Automated Data Augmentation Algorithms for Deep Learning-based Image Classification Tasks","created":"2022-06-14","cited_by_count":12,"area":null},{"id":"2411.00247","title":"Deep Learning Through A Telescoping Lens: A Simple Model Provides Empirical Insights On Grokking, Gradient Boosting & Beyond","created":"2024-10-31","cited_by_count":9,"area":null},{"id":"2107.08714","title":"CETransformer: Casual Effect Estimation via Transformer Based Representation Learning","created":"2021-07-19","cited_by_count":8,"area":null},{"id":"2210.09809","title":"Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel","created":"2022-10-18","cited_by_count":8,"area":null},{"id":"2305.14585","title":"Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models","created":"2023-05-23","cited_by_count":8,"area":null},{"id":"2207.06080","title":"Efficient Augmentation for Imbalanced Deep Learning","created":"2022-07-13","cited_by_count":6,"area":null},{"id":"2211.03566","title":"Can neural networks extrapolate? Discussion of a theorem by Pedro Domingos","created":"2022-11-07","cited_by_count":6,"area":null},{"id":"2406.06207","title":"Lurking in the shadows: Unveiling Stealthy Backdoor Attacks against Personalized Federated Learning","created":"2024-06-10","cited_by_count":6,"area":null},{"id":"2307.01177","title":"Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space","created":"2023-07-03","cited_by_count":5,"area":null},{"id":"2308.00824","title":"An Exact Kernel Equivalence for Finite Classification Models","created":"2023-08-01","cited_by_count":5,"area":null},{"id":"2110.01326","title":"ACDC: Online Unsupervised Cross-Domain Adaptation","created":"2021-10-04","cited_by_count":4,"area":null},{"id":"2110.04060","title":"New Insights into Graph Convolutional Networks using Neural Tangent Kernels","created":"2021-10-08","cited_by_count":4,"area":null},{"id":"2212.11826","title":"The Quantum Path Kernel: a Generalized Quantum Neural Tangent Kernel for Deep Quantum Machine Learning","created":"2022-12-22","cited_by_count":4,"area":null},{"id":"2205.12372","title":"TorchNTK: A Library for Calculation of Neural Tangent Kernels of PyTorch Models","created":"2022-05-24","cited_by_count":3,"area":null},{"id":"2409.11140","title":"Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations","created":"2024-09-17","cited_by_count":3,"area":null},{"id":"2410.16292","title":"An evaluation of LLM code generation capabilities through graded exercises","created":"2024-10-06","cited_by_count":3,"area":null},{"id":"2505.20076","title":"ExPLAIND: Unifying Model, Data, and Training Attribution to Study Model Behavior","created":"2025-05-26","cited_by_count":3,"area":null},{"id":"2209.15562","title":"On the optimization and generalization of overparameterized implicit neural networks","created":"2022-09-30","cited_by_count":2,"area":null},{"id":"2506.16283","title":"Random feature approximation for general spectral methods","created":"2025-06-19","cited_by_count":2,"area":null},{"id":"2601.22563","title":"EUGens: Efficient, Unified, and General Dense Layers","created":"2026-01-30","cited_by_count":2,"area":null},{"id":"2208.12814","title":"Interpretable (not just posthoc-explainable) medical claims modeling for discharge placement to prevent avoidable all-cause readmissions or death","created":"2022-08-28","cited_by_count":1,"area":null},{"id":"2304.05895","title":"Towards Understanding How Data Augmentation Works with Imbalanced Data","created":"2023-04-12","cited_by_count":1,"area":null},{"id":"2603.13872","title":"On Interpolation Formulas Describing Neural Network Generalization","created":"2026-03-14","cited_by_count":1,"area":null},{"id":"2104.05874","title":"Gradient Kernel Regression","created":"2021-04-13","cited_by_count":0,"area":null},{"id":"2110.11911","title":"Self-supervised denoising for massive noisy images","created":"2021-10-18","cited_by_count":0,"area":null},{"id":"2307.07575","title":"A Quantitative Approach to Predicting Representational Learning and Performance in Neural Networks","created":"2023-07-14","cited_by_count":0,"area":null},{"id":"2308.15434","title":"Random feature approximation for general spectral methods","created":"2023-08-29","cited_by_count":0,"area":null},{"id":"2406.00509","title":"Empirical influence functions to understand the logic of fine-tuning","created":"2024-06-01","cited_by_count":0,"area":null},{"id":"2410.06921","title":"Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility","created":"2024-10-09","cited_by_count":0,"area":null},{"id":"2410.09771","title":"EUGens: Efficient, Unified, and General Dense Layers","created":"2024-10-13","cited_by_count":0,"area":null},{"id":"2506.02406","title":"Random at First, Fast at Last: NTK-Guided Fourier Pre-Processing for Tabular DL","created":"2025-06-03","cited_by_count":0,"area":null},{"id":"2603.02843","title":"Scale-invariant Gaussian derivative residual networks","created":"2026-03-03","cited_by_count":0,"area":null},{"id":"2606.07495","title":"Second-Order Path Kernel Interpolation Formulas in Machine Learning","created":"2026-06-05","cited_by_count":0,"area":null},{"id":"2610.03858","title":"Retrieval-Centric Deep Learning in Growing Nonparametric Neural Networks","created":"2026-10-02","cited_by_count":0,"area":null},{"id":"2610.13568","title":"Rationally Linearized MLPs","created":"2026-10-09","cited_by_count":0,"area":null}],"next_cursor":null}