zeke-xie / artificial-neural-variability-for-deep-learning
[Neural Computation, MIT Press] The PyTorch Implementation of Variable Optimizers/ Neural Variable Risk Minimization proposed in our Neural Computation paper: Artificial Neural Variability for Deep Learning: On overfitting, Noise Memorization, and Catastrophic Forgetting.
☆33Updated 3 years ago
Alternatives and similar repositories for artificial-neural-variability-for-deep-learning:
Users that are interested in artificial-neural-variability-for-deep-learning are comparing it to the libraries listed below
- [ICML 2021] The official PyTorch Implementations of Positive-Negative Momentum Optimizers.☆28Updated 2 years ago
- [NeurIPS 2023] The PyTorch Implementation of Scheduled (Stable) Weight Decay.☆59Updated last year
- ☆34Updated last week
- Implementation of Effective Sparsification of Neural Networks with Global Sparsity Constraint☆31Updated 3 years ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 2 years ago
- Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"☆36Updated 2 years ago
- ☆19Updated 5 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆49Updated 4 years ago
- Gradients as Features for Deep Representation Learning☆43Updated 5 years ago
- Code for "Just Train Twice: Improving Group Robustness without Training Group Information"☆71Updated 11 months ago
- ☆57Updated 2 years ago
- Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…☆53Updated 3 years ago
- Code for "The Intrinsic Dimension of Images and Its Impact on Learning" - ICLR 2021 Spotlight https://openreview.net/forum?id=XJk19XzGq2J☆68Updated last year
- Code for the paper "Understanding Generalization through Visualizations"☆60Updated 4 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆121Updated 3 years ago
- Weight-Averaged Sharpness-Aware Minimization (NeurIPS 2022)☆28Updated 2 years ago
- Visualization of mean field and neural tangent kernel regime☆20Updated 9 months ago
- [NeurIPS 2021] A Geometric Analysis of Neural Collapse with Unconstrained Features☆56Updated 2 years ago
- This framework implements key experiments on the sparse double descent phenomenon (ICML 2022).☆14Updated 2 years ago
- Project for the Large Scale Optimization course at Skoltech☆22Updated 6 years ago
- implements optimal transport algorithms in pytorch☆96Updated 2 years ago
- Tensorflow implementation of "Meta Dropout: Learning to Perturb Latent Features for Generalization" (ICLR 2020)☆27Updated 4 years ago
- PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"☆74Updated 5 years ago
- A Self-Consistent Robust Error (ICML 2022)☆67Updated last year
- Towards increasing stability of neural networks for continual learning: https://arxiv.org/abs/2006.06958.pdf (NeurIPS'20)☆75Updated 2 years ago
- ICLR 2021, Fair Mixup: Fairness via Interpolation☆55Updated 3 years ago
- Pytorch Implementation of the Nonlinear Information Bottleneck☆39Updated 9 months ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆23Updated 3 years ago
- ☆58Updated 2 years ago
- Code for paper "Orthogonal Convolutional Neural Networks".☆116Updated 3 years ago