{"total":31,"rows":[{"id":"2109.02934","title":"Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization","created":"2021-09-07","cited_by_count":186,"area":null},{"id":"2207.12678","title":"Analyzing Sharpness along GD Trajectory: Progressive Sharpening and Edge of Stability","created":"2022-07-26","cited_by_count":63,"area":null},{"id":"2201.12250","title":"Gradient Descent on Neurons and its Link to Approximate Second-Order Optimization","created":"2022-01-28","cited_by_count":30,"area":null},{"id":"2208.04924","title":"On the Activation Function Dependence of the Spectral Bias of Neural Networks","created":"2022-08-09","cited_by_count":28,"area":null},{"id":"2309.16932","title":"Symmetry Induces Structure and Constraint of Learning","created":"2023-09-29","cited_by_count":25,"area":null},{"id":"2312.00359","title":"Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training","created":"2023-12-01","cited_by_count":20,"area":null},{"id":"2312.12226","title":"On the Parameterization of Second-Order Optimization Effective Towards the Infinite Width","created":"2023-12-19","cited_by_count":15,"area":null},{"id":"2206.02927","title":"Spectral Bias Outside the Training Set for Deep Networks in the Kernel Regime","created":"2022-06-06","cited_by_count":11,"area":null},{"id":"2402.05379","title":"Trade-Offs of Diagonal Fisher Information Matrix Estimators","created":"2024-02-08","cited_by_count":10,"area":null},{"id":"2104.13289","title":"Model-centric Data Manifold: the Data Through the Eyes of the Model","created":"2021-04-26","cited_by_count":9,"area":null},{"id":"2509.22335","title":"Spectral Collapse Drives Loss of Plasticity in Deep Continual Learning","created":"2025-09-26","cited_by_count":6,"area":null},{"id":"2301.05785","title":"Efficient Activation Function Optimization through Surrogate Modeling","created":"2023-01-13","cited_by_count":5,"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":"2502.04975","title":"Training-free Neural Architecture Search through Variance of Knowledge of Deep Network Weights","created":"2025-02-07","cited_by_count":3,"area":null},{"id":"2506.07661","title":"Information-Theoretic Framework for Understanding Modern Machine-Learning","created":"2025-06-09","cited_by_count":3,"area":null},{"id":"2601.21929","title":"LoRIF: Low-Rank Influence Functions for Scalable Training Data Attribution","created":"2026-01-29","cited_by_count":3,"area":null},{"id":"2606.19491","title":"Algebraic Dead Directions in LayerNorm Transformers: A Forward-Pass-Only Diagnostic at LLM Scale","created":"2026-06-17","cited_by_count":3,"area":null},{"id":"2407.17834","title":"Towards the Spectral bias Alleviation by Normalizations in Coordinate Networks","created":"2024-07-25","cited_by_count":2,"area":null},{"id":"2410.04264","title":"Decoupling Dynamical Richness from Representation Learning: Towards Practical Measurement","created":"2024-10-05","cited_by_count":2,"area":null},{"id":"2606.21158","title":"Dead-Direction Signatures: A Cheap Spectral Reading of Singular Complexity","created":"2026-06-19","cited_by_count":2,"area":null},{"id":"2205.03343","title":"Far from Asymptopia","created":"2022-05-06","cited_by_count":1,"area":null},{"id":"2603.29466","title":"An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms","created":"2026-03-31","cited_by_count":1,"area":null},{"id":"2605.11316","title":"Error whitening: Why Gauss-Newton outperforms Newton","created":"2026-05-11","cited_by_count":1,"area":null},{"id":"2202.05254","title":"Deep Learning in Random Neural Fields: Numerical Experiments via Neural Tangent Kernel","created":"2022-02-10","cited_by_count":0,"area":null},{"id":"2406.18137","title":"Sparse deep neural networks for nonparametric estimation in high-dimensional sparse regression","created":"2024-06-26","cited_by_count":0,"area":null},{"id":"2505.13614","title":"Deterministic Bounds and Random Estimates of Metric Tensors on Neuromanifolds","created":"2025-05-19","cited_by_count":0,"area":null},{"id":"2510.06945","title":"Fisher Information, Training and Bias in Fourier Regression Models","created":"2025-10-08","cited_by_count":0,"area":null},{"id":"2605.31324","title":"Inconsistency-Aware Minimization: Improving Generalization with Unlabeled Data","created":"2026-05-29","cited_by_count":0,"area":null},{"id":"2606.06171","title":"Effective Dimensionality as an Operator Invariant for Physics-Preserving Constraint Adaptation in Physics-Informed Neural Networks","created":"2026-06-04","cited_by_count":0,"area":null},{"id":"2607.07845","title":"Explaining Near-Zero Hessian Eigenvalues Through Approximate Symmetries in Neural Networks","created":"2026-07-08","cited_by_count":0,"area":null},{"id":"2608.21561","title":"Loss-Parameterized Fisher Width Along Learning Trajectories","created":"2026-08-21","cited_by_count":0,"area":null}],"next_cursor":null}