geifmany / selectivenetLinks
code for the ICML paper "SelectiveNet - A Deep Neural Network with an Integrated Reject Option"
☆46Updated 6 years ago
Alternatives and similar repositories for selectivenet
Users that are interested in selectivenet are comparing it to the libraries listed below
Sorting:
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆91Updated 5 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- ☆83Updated 2 years ago
- Self-Explaining Neural Networks☆13Updated 2 years ago
- ☆63Updated 5 years ago
- Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and featu…☆43Updated 5 years ago
- Winning Solution of the NeurIPS 2020 Competition on Predicting Generalization in Deep Learning☆41Updated 4 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- PyTorch Implementations of Dropout Variants☆88Updated 7 years ago
- Official PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.☆143Updated last year
- Tensorflow implementation of "Learning to Balance: Bayesian Meta-learning for Imbalanced and Out-of-distribution Tasks" (ICLR 2020 oral)☆101Updated 5 years ago
- [TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training☆130Updated 4 years ago
- ☆40Updated 5 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆50Updated 4 years ago
- Official code for the paper "Task2Vec: Task Embedding for Meta-Learning" (https://arxiv.org/abs/1902.03545, ICCV 2019)☆124Updated 2 years ago
- Robust Out-of-distribution Detection in Neural Networks☆73Updated 3 years ago
- Tensorflow implementation of "Meta Dropout: Learning to Perturb Latent Features for Generalization" (ICLR 2020)☆27Updated 5 years ago
- [ICLR 2021] Concept Learners for Few-Shot Learning☆115Updated 2 years ago
- ☆96Updated 4 years ago
- [NeurIPS 2020] Coresets for Robust Training of Neural Networks against Noisy Labels☆35Updated 4 years ago
- Outlier Exposure with Confidence Control for Out-of-Distribution Detection☆71Updated 4 years ago
- This repo provides code used in the paper "Predicting with High Correlation Features" (https://arxiv.org/abs/1910.00164):☆54Updated 8 months ago
- ☆57Updated 4 years ago
- pytorch implementation of manifold-mixup☆22Updated 3 years ago
- Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018☆182Updated 5 years ago
- Coresets via Bilevel Optimization☆68Updated 5 years ago
- Python codes for influential instance estimation☆56Updated 3 years ago
- Implementation of the paper "Shapley Explanation Networks"☆89Updated 4 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆91Updated 5 years ago
- A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks☆233Updated 7 years ago