jfc43 / self-training-ensembles
Propose a principled and practically effective framework for unsupervised accuracy estimation and error detection tasks with theoretical analysis and state-of-the-art performance.
☆14Updated 3 years ago
Alternatives and similar repositories for self-training-ensembles:
Users that are interested in self-training-ensembles are comparing it to the libraries listed below
- Latent Discriminant deterministic Uncertainty [ECCV2022]☆41Updated 2 years ago
- [NeurIPS21] TTT++: When Does Self-supervised Test-time Training Fail or Thrive?☆67Updated 3 years ago
- Automatic model evaluation (AutoEval) in CVPR'21&TPAMI'22☆36Updated 2 years ago
- On the Importance of Gradients for Detecting Distributional Shifts in the Wild☆56Updated 2 years ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆23Updated 3 years ago
- The Official Implementation of the ICCV-2021 Paper: Semantically Coherent Out-of-Distribution Detection.☆70Updated 3 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆121Updated 3 years ago
- Code for CVPR2021 paper: MOOD: Multi-level Out-of-distribution Detection☆38Updated last year
- This repository provides code for "On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness".☆45Updated 2 years ago
- [TPAMI 2019] The implementation for "Direction Concentration Learning: Enhancing Congruency in Machine Learning"☆23Updated 5 years ago
- [ICML'21] Estimate the accuracy of the classifier in various environments through self-supervision☆27Updated 3 years ago
- Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization☆86Updated 2 years ago
- Predicting Out-of-Distribution Error with the Projection Norm☆17Updated 2 years ago
- Repo for the paper "Extrapolating from a Single Image to a Thousand Classes using Distillation"☆36Updated 9 months ago
- Visual Representation Learning Benchmark for Self-Supervised Models☆36Updated last year
- Robustness via Cross-Domain Ensembles, ICCV 2021 [Oral]☆39Updated 3 years ago
- ☆32Updated 3 years ago
- ☆57Updated 2 years ago
- ☆31Updated 3 years ago
- This code accompanies the paper "Parameter-free Online Test-time Adaptation".☆69Updated 2 years ago
- [ECCV2022] The PyTorch implementation of paper "Equivariance and Invariance Inductive Bias for Learning from Insufficient Data"☆19Updated 2 years ago
- ☆45Updated 3 years ago
- ☆23Updated 2 years ago
- This is a public repository for:☆38Updated 3 years ago
- ☆21Updated 5 years ago
- Pytorch implementation of regularization methods for deep networks obtained via kernel methods.☆22Updated 5 years ago
- Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"☆36Updated 2 years ago
- Code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning", Ren et al., NeurIPS'20☆25Updated 4 years ago
- Metrics for "Beyond neural scaling laws: beating power law scaling via data pruning " (NeurIPS 2022 Outstanding Paper Award)☆56Updated 2 years ago
- The official code for the NeurIPS 2021 paper Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels (https://arxiv.org…☆22Updated 3 years ago