salesforce / corr_based_predictionLinks
This repo provides code used in the paper "Predicting with High Correlation Features" (https://arxiv.org/abs/1910.00164):
☆54Updated last month
Alternatives and similar repositories for corr_based_prediction
Users that are interested in corr_based_prediction are comparing it to the libraries listed below
Sorting:
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 5 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆89Updated 5 years ago
- Unofficial pytorch implementation of a paper, Distributional Smoothing with Virtual Adversarial Training [Miyato+, ICLR2016].☆26Updated 7 years ago
- Official adversarial mixup resynthesis repository☆35Updated 5 years ago
- Code for paper "Dimensionality-Driven Learning with Noisy Labels" - ICML 2018☆58Updated last year
- Unofficial pytorch implementation of Born-Again Neural Networks.☆54Updated 4 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
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated 2 years ago
- Code for Unsupervised Learning via Meta-Learning.☆66Updated 4 years ago
- Official Implementation of "Random Path Selection for Incremental Learning" paper. NeurIPS 2019☆53Updated 2 years ago
- This repo contains the code used for NeurIPS 2019 paper "Asymmetric Valleys: Beyond Sharp and Flat Local Minima".☆14Updated 5 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆91Updated 4 years ago
- Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018☆22Updated 5 years ago
- ☆63Updated 4 years ago
- [TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training☆128Updated 3 years ago
- Gradients as Features for Deep Representation Learning☆43Updated 5 years ago
- Gold Loss Correction☆87Updated 6 years ago
- Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"☆38Updated 6 years ago
- Implementation of Bayesian Gradient Descent☆37Updated last year
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (IMM)☆35Updated 7 years ago
- PyTorch Implementation of Neural Statistician☆60Updated 3 years ago
- A DIRT-T Approach to Unsupervised Domain Adaptation (ICLR 2018)☆175Updated 7 years ago
- Improving MMD-GAN training with repulsive loss function☆89Updated 2 years ago
- Official code for ICLR 2020 paper "A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning."☆100Updated 4 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Improving Consistency-Based Semi-Supervised Learning with Weight Averaging☆186Updated 6 years ago
- Code for the paper: On Symmetric Losses for Learning from Corrupted Labels☆19Updated 6 years ago
- Robust loss functions for deep neural networks (CVPR 2017)☆91Updated 5 years ago
- Full implementation of the paper "Rethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information Estimator".☆102Updated 5 years ago