atuannguyen / DIRT
☆10Updated 2 years ago
Related projects: ⓘ
- Official Python3 implementation of our ICML 2021 paper "Unbalanced minibatch Optimal Transport; applications to Domain Adaptation"☆42Updated 2 years ago
- [CLeaR23] Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning☆29Updated last year
- Keypoint-Guided Optimal Transport (NeurIPS 2022)☆21Updated last year
- [ICML 2023] Offical implementation of the paper "Uncertainty Estimation by Fisher Information-based Evidential Deep Learning".☆32Updated last year
- PyTorch code for Uncertainty-guided Source-free Domain Adaptation☆34Updated 2 years ago
- [ICML2023] InfoOT: Information Maximizing Optimal Transport☆40Updated last year
- PyTorch Implementation for Gromov-Wasserstein Autoencoders (GWAE)☆40Updated last year
- Contrastive Variational Autoencoders☆61Updated 5 years ago
- A new mini-batch framework for optimal transport in deep generative models, deep domain adaptation, approximate Bayesian computation, col…☆35Updated last year
- MetaMix for ICML 2021☆27Updated 3 years ago
- ☆18Updated 2 years ago
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆26Updated last year
- Pytorch code release of CVPR 21 Paper: Learning Invariant Representations and Risks☆32Updated 3 years ago
- Functional Optimal Transport: Map Estimation and Domain Adaptation for Functional data☆24Updated 3 years ago
- Latent optimal transport (LOT) for low rank transport and clustering☆20Updated 3 years ago
- Official PyTorch implementation of 🏁 MFCVAE 🏁: "Multi-Facet Clustering Variatonal Autoencoders (MFCVAE)" (NeurIPS 2021). A class of var…☆38Updated last year
- Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022☆18Updated 2 years ago
- Official implementation of "How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?", TMLR 2023.☆18Updated 5 months ago
- Source code for the NeurIPS 2023 paper: "CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with Noisy Labels"☆18Updated 9 months ago
- Contains the code relative to the paper Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning https://arxiv.org/abs…☆20Updated 4 years ago
- Source code of a ICML2021 paper, A Bit More Bayesian: Domain-Invariant Learning with Uncertainty☆11Updated 2 years ago
- Benchmark and analysis of 165 pretrained SSL models. Code for "Evaluating Self-Supervised Learning via Risk Decomposition".☆13Updated last year
- PyTorch Implementation - Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction☆31Updated 2 years ago
- A Variational Information Bottleneck Approach to Multi-Omics Data Integration☆21Updated 3 years ago
- GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning☆33Updated 2 years ago
- Learning Representations that Support Robust Transfer of Predictors☆20Updated 2 years ago
- Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)☆20Updated last year
- C-Mixup for NeurIPS 2022☆62Updated 9 months ago
- Code Release for Learning to Adapt to Evolving Domains☆30Updated 3 years ago
- ☆11Updated last year