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 4 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.☆27Updated 3 years ago
- ☆34Updated 6 months ago
- Official Implementation of Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction (2020)☆202Updated 3 years ago
- Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…☆53Updated 4 years ago
- Continual Learning in Low-rank Orthogonal Subspaces (NeurIPS'20)☆37Updated 5 years ago
- Code for "Just Train Twice: Improving Group Robustness without Training Group Information"☆73Updated last year
- Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization☆89Updated 3 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆123Updated 4 years ago
- Towards increasing stability of neural networks for continual learning: https://arxiv.org/abs/2006.06958.pdf (NeurIPS'20)☆76Updated 2 years ago
- ☆42Updated 5 years ago
- Implementation of Inexact Proximal point method for Optimal Transport☆50Updated 4 years ago
- Code for the paper "Understanding Generalization through Visualizations"☆65Updated 4 years ago
- ☆81Updated last year
- [ICLR 2021] Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization☆42Updated 4 years ago
- Pytorch implementation for "The Surprising Positive Knowledge Transfer in Continual 3D Object Shape Reconstruction"☆33Updated 3 years ago
- Code for NeurIPS 2020 Paper --- Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks☆21Updated 3 years ago
- Code for "Generalisation Guarantees for Continual Learning with Orthogonal Gradient Descent" (ICML 2020 - Lifelong Learning Workshop)☆44Updated 3 years ago
- Official [ICLR] Code Repository for "Gradient Projection Memory for Continual Learning"☆99Updated 4 years ago
- Official code for ICLR 2020 paper "A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning."☆101Updated 5 years ago
- The official PyTorch implementation of the paper: Xili Dai, Shengbang Tong, et al. "Closed-Loop Data Transcription to an LDR via Minimaxi…☆64Updated 3 years ago
- A Tensorflow implementation Mutual Information estimation methods☆48Updated 2 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- ☆23Updated 3 years ago
- Gradients as Features for Deep Representation Learning☆43Updated 5 years ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆37Updated 3 years ago
- Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxi…☆68Updated 4 years ago
- Visualization of mean field and neural tangent kernel regime☆21Updated last year
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆91Updated 5 years ago
- [NeurIPS 2023] The PyTorch Implementation of Scheduled (Stable) Weight Decay.☆61Updated last year
- ☆37Updated 4 years ago