{"total":18,"rows":[{"id":"2111.00034","title":"Neural Networks as Kernel Learners: The Silent Alignment Effect","created":"2021-10-29","cited_by_count":106,"area":null},{"id":"2405.00592","title":"Scaling and renormalization in high-dimensional regression","created":"2024-05-01","cited_by_count":50,"area":null},{"id":"2302.06755","title":"Dataset Distillation with Convexified Implicit Gradients","created":"2023-02-13","cited_by_count":46,"area":null},{"id":"2105.14301","title":"A Theory of Neural Tangent Kernel Alignment and Its Influence on Training","created":"2021-05-29","cited_by_count":25,"area":null},{"id":"2203.00573","title":"Contrasting random and learned features in deep Bayesian linear regression","created":"2022-03-01","cited_by_count":24,"area":null},{"id":"2102.08668","title":"Non-asymptotic approximations of neural networks by Gaussian processes","created":"2021-02-17","cited_by_count":19,"area":null},{"id":"2210.04909","title":"Meta-Principled Family of Hyperparameter Scaling Strategies","created":"2022-10-10","cited_by_count":19,"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":"2302.01428","title":"Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation","created":"2023-02-02","cited_by_count":14,"area":null},{"id":"2111.03175","title":"Rate of Convergence of Polynomial Networks to Gaussian Processes","created":"2021-11-04","cited_by_count":13,"area":null},{"id":"2305.02334","title":"Structures of Neural Network Effective Theories","created":"2023-05-03","cited_by_count":13,"area":null},{"id":"2304.04010","title":"Non-asymptotic approximations of Gaussian neural networks via second-order Poincar\\'e inequalities","created":"2023-04-08","cited_by_count":11,"area":null},{"id":"2502.03210","title":"From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning","created":"2025-02-05","cited_by_count":10,"area":null},{"id":"2108.02316","title":"Deep Stable neural networks: large-width asymptotics and convergence rates","created":"2021-08-02","cited_by_count":8,"area":null},{"id":"2111.12143","title":"Critical Initialization of Wide and Deep Neural Networks through Partial Jacobians: General Theory and Applications","created":"2021-11-23","cited_by_count":8,"area":null},{"id":"2104.11734","title":"Exact marginal prior distributions of finite Bayesian neural networks","created":"2021-04-23","cited_by_count":1,"area":null},{"id":"2602.04548","title":"Gradient Flow Through Diagram Expansions: Learning Regimes and Explicit Solutions","created":"2026-02-04","cited_by_count":1,"area":null},{"id":"2608.19584","title":"K\\\"ahler landscapes for complex neural network descents and guarantees including a search and destroy of the Calabi-Yau manifold","created":"2026-08-20","cited_by_count":0,"area":null}],"next_cursor":null}