zeke-xie / artificial-neural-variability-for-deep-learningLinks
[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
Sorting:
- [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
- Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization☆86Updated 3 years ago
- Robust Optimal Transport code☆43Updated 2 years ago
- Project for the Large Scale Optimization course at Skoltech☆22Updated 6 years ago
- Code for NeurIPS 2020 Paper --- Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks☆21Updated 2 years ago
- A Tensorflow implementation Mutual Information estimation methods☆47Updated 2 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆122Updated 3 years ago
- Weighted Training for Cross-Task Learning☆15Updated 2 years ago
- The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)☆40Updated last year
- ☆14Updated 4 years ago
- Computing various measures and generalization bounds on convolutional and fully connected networks☆35Updated 6 years ago
- Improving Transformation Invariance in Contrastive Representation Learning☆13Updated 4 years ago
- ☆36Updated 3 years ago
- The official PyTorch implementation of the paper: Xili Dai, Shengbang Tong, et al. "Closed-Loop Data Transcription to an LDR via Minimaxi…☆63Updated 2 years ago
- ☆58Updated 2 years ago
- Code for "Generalisation Guarantees for Continual Learning with Orthogonal Gradient Descent" (ICML 2020 - Lifelong Learning Workshop)☆42Updated 2 years ago
- Towards increasing stability of neural networks for continual learning: https://arxiv.org/abs/2006.06958.pdf (NeurIPS'20)☆75Updated 2 years ago
- ☆37Updated 4 years ago
- This framework implements key experiments on the sparse double descent phenomenon (ICML 2022).☆14Updated 2 years ago
- ☆34Updated last week
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 2 years ago
- Code for ICLR 2019 Paper, "MAX-MIG: AN INFORMATION THEORETIC APPROACH FOR JOINT LEARNING FROM CROWDS"☆25Updated 2 years ago
- Example implementation for the paper: (ICLR Oral) Learning Robust Representations by Projecting Superficial Statistics Out☆27Updated 4 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆50Updated 3 years ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆24Updated 3 years ago
- Weight-Averaged Sharpness-Aware Minimization (NeurIPS 2022)☆28Updated 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
- ICLR 2021: Noise against noise: stochastic label noise helps combat inherent label noise☆14Updated 4 years ago
- Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"☆36Updated 2 years ago