{"total":21,"rows":[{"id":"2302.00375","title":"Bayes-optimal Learning of Deep Random Networks of Extensive-width","created":"2023-02-01","cited_by_count":41,"area":null},{"id":"2312.15995","title":"Generalization in Kernel Regression Under Realistic Assumptions","created":"2023-12-26","cited_by_count":27,"area":null},{"id":"2309.04268","title":"Optimal Rate of Kernel Regression in Large Dimensions","created":"2023-09-08","cited_by_count":11,"area":null},{"id":"2208.09897","title":"Multiple Descent in the Multiple Random Feature Model","created":"2022-08-21","cited_by_count":10,"area":null},{"id":"2310.01975","title":"Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks for XOR Data","created":"2023-10-03","cited_by_count":10,"area":null},{"id":"2404.12597","title":"The phase diagram of kernel interpolation in large dimensions","created":"2024-04-19","cited_by_count":9,"area":null},{"id":"2505.24849","title":"Statistical mechanics of extensive-width Bayesian neural networks near interpolation","created":"2025-05-30","cited_by_count":9,"area":null},{"id":"2211.06077","title":"Overparameterized random feature regression with nearly orthogonal data","created":"2022-11-11","cited_by_count":7,"area":null},{"id":"2409.03891","title":"Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality","created":"2024-09-05","cited_by_count":7,"area":null},{"id":"2402.10164","title":"Random features and polynomial rules","created":"2024-02-15","cited_by_count":6,"area":null},{"id":"2212.06757","title":"Gradient flow in the gaussian covariate model: exact solution of learning curves and multiple descent structures","created":"2022-12-13","cited_by_count":5,"area":null},{"id":"2305.14689","title":"Least Squares Regression Can Exhibit Under-Parameterized Double Descent","created":"2023-05-24","cited_by_count":4,"area":null},{"id":"2409.00915","title":"On the Pinsker bound of inner product kernel regression in large dimensions","created":"2024-09-02","cited_by_count":2,"area":null},{"id":"2503.00504","title":"On the Saturation Effects of Spectral Algorithms in Large Dimensions","created":"2025-03-01","cited_by_count":2,"area":null},{"id":"2210.01257","title":"Testing predictions of representation cost theory with CNNs","created":"2022-10-03","cited_by_count":0,"area":null},{"id":"2412.18756","title":"Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories","created":"2024-12-25","cited_by_count":0,"area":null},{"id":"2505.19019","title":"Querying Kernel Methods Suffices for Reconstructing their Training Data","created":"2025-05-25","cited_by_count":0,"area":null},{"id":"2510.17120","title":"Matricial Free Energy as a Gaussianizing Regularizer: Enhancing Autoencoders for Gaussian Code Generation","created":"2025-10-20","cited_by_count":0,"area":null},{"id":"2510.24616","title":"Statistical physics of deep learning: Optimal learning of a multi-layer perceptron near interpolation","created":"2025-10-28","cited_by_count":0,"area":null},{"id":"2601.23208","title":"A Random Matrix Theory of Masked Self-Supervised Regression","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2609.33675","title":"Benign Overfitting for General Norms and Distributions","created":"2026-09-27","cited_by_count":0,"area":null}],"next_cursor":null}