nsfzyzz / Generalization_metrics_for_NLP
[KDD 2023] code for "Test accuracy vs. generalization gap: model selection in NLP without accessing training or testing data" https://arxiv.org/pdf/2202.02842.pdf
☆12Updated last year
Related projects: ⓘ
- Efficient empirical NTKs in PyTorch☆15Updated 2 years ago
- [NeurIPS 2023 Spotlight] Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training☆24Updated 9 months ago
- ☆56Updated 3 years ago
- Influence Functions with (Eigenvalue-corrected) Kronecker-Factored Approximate Curvature☆93Updated last month
- Neural Tangent Kernel Papers☆84Updated 6 months ago
- A fast, effective data attribution method for neural networks in PyTorch☆170Updated this week
- Source code of "Task arithmetic in the tangent space: Improved editing of pre-trained models".☆79Updated last year
- This is an official repository for "LAVA: Data Valuation without Pre-Specified Learning Algorithms" (ICLR2023).☆40Updated 3 months ago
- [NeurIPS 2021] code for "Taxonomizing local versus global structure in neural network loss landscapes" https://arxiv.org/abs/2107.11228☆18Updated 2 years ago
- Code for "The Intrinsic Dimension of Images and Its Impact on Learning" - ICLR 2021 Spotlight https://openreview.net/forum?id=XJk19XzGq2J☆63Updated 5 months ago
- ☆187Updated 4 months ago
- An Investigation of Why Overparameterization Exacerbates Spurious Correlations☆30Updated 4 years ago
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆42Updated last year
- {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch☆204Updated last month
- Source code of "What can linearized neural networks actually say about generalization?☆17Updated 2 years ago
- ☆31Updated 7 months ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆34Updated 2 years ago
- A simple PyTorch implementation of influence functions.☆75Updated 3 months ago
- Code for the paper: "Tensor Programs II: Neural Tangent Kernel for Any Architecture"☆93Updated 4 years ago
- Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians (ICML 2019)☆17Updated 5 years ago
- Landing Page for TOFU☆79Updated 3 months ago
- The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)☆39Updated 7 months ago
- ☆61Updated 3 years ago
- Code release for REPAIR: REnormalizing Permuted Activations for Interpolation Repair☆43Updated 7 months ago
- ☆14Updated last year
- Weight-Averaged Sharpness-Aware Minimization (NeurIPS 2022)☆25Updated last year
- [NeurIPS 2021] A Geometric Analysis of Neural Collapse with Unconstrained Features☆50Updated 2 years ago
- Training vision models with full-batch gradient descent and regularization☆37Updated last year
- Influence Analysis and Estimation - Survey, Papers, and Taxonomy☆58Updated 6 months ago
- Git Re-Basin: Merging Models modulo Permutation Symmetries in PyTorch☆69Updated last year