wangwllu / provably_robust_metric_learning
A metric learning method to learn a provably robust Mahalanobis distance
☆10Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for provably_robust_metric_learning
- Code Release for Learning to Adapt to Evolving Domains☆30Updated 3 years ago
- [ICLR 2021] Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization☆40Updated 3 years ago
- This repository is the official implementation of Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regulari…☆21Updated last year
- ☆30Updated 3 years ago
- [NeurIPS 2021] “Improving Contrastive Learning on Imbalanced Data via Open-World Sampling”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangya…☆28Updated 2 years ago
- ☆40Updated 4 years ago
- ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust☆13Updated 3 years ago
- ☆18Updated 3 years ago
- ☆12Updated 5 years ago
- Pytorch implementation for "The Surprising Positive Knowledge Transfer in Continual 3D Object Shape Reconstruction"☆33Updated 2 years ago
- ☆17Updated 2 years ago
- [ICLR 2021] "Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, S…☆23Updated 2 years ago
- Self-Distillation with weighted ground-truth targets; ResNet and Kernel Ridge Regression☆17Updated 3 years ago
- This repository hosts the dataset and source code for "A causal view of compositional zero-shot recognition". Yuval Atzmon, Felix Kreuk, …☆27Updated 3 years ago
- Robust Contrastive Learning Using Negative Samples with Diminished Semantics (NeurIPS 2021)☆39Updated 2 years ago
- Implementation of the paper Identifying Mislabeled Data using the Area Under the Margin Ranking: https://arxiv.org/pdf/2001.10528v2.pdf☆21Updated 4 years ago
- PyTorch implementation of the paper "SuperLoss: A Generic Loss for Robust Curriculum Learning" in NIPS 2020.☆30Updated 3 years ago
- Code release for Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning (NeurIPS 2019)☆24Updated 2 years ago
- PyTorch code for NeurIPSW 2020 paper (4th Workshop on Meta-Learning) "Few-Shot Unsupervised Continual Learning through Meta-Examples"☆20Updated 4 years ago
- Domain Adaptation as a Problem of Inference on Graphical Models☆29Updated 3 years ago
- Code for the article "Confidence Scores Make Instance-dependent Label-noise Learning Possible", ICML'21☆9Updated 3 months ago
- Code implementation for paper "On the Efficacy of Small Self-Supervised Contrastive Models without Distillation Signals".☆16Updated 2 years ago
- Code for the ICLR 2022 paper "Attention-based interpretability with Concept Transformers"☆39Updated last year
- ☆27Updated 3 years ago
- Class Incremental learning, Task Incremental Learning☆16Updated last year
- ☆26Updated 2 years ago
- PyTorch implementation of "Online Hyperparameter Optimization for Class-Incremental Learning" (AAAI 2023 Oral)☆17Updated last year
- Official implementation of paper Gradient Matching for Domain Generalization☆116Updated 2 years ago
- Class Normalization for Continual Zero-Shot Learning☆34Updated 3 years ago
- Example implementation for the paper: (ICLR Oral) Learning Robust Representations by Projecting Superficial Statistics Out☆27Updated 3 years ago