MaheepChaudhary / Causality-in-Trustworthy-Machine-Learning
The repository contains lists of papers on causality and how relevant techniques are being used to further enhance deep learning era computer vision solutions.
☆83Updated last year
Related projects ⓘ
Alternatives and complementary repositories for Causality-in-Trustworthy-Machine-Learning
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆99Updated last year
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆128Updated last year
- Analysis of evidential models☆11Updated last year
- Code for Diff-SCM paper☆94Updated last year
- ☆97Updated 3 years ago
- Official implementation for "Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition" (I…☆39Updated last year
- Experiments to reproduce results in Interventional Causal Representation Learning.☆25Updated last year
- Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off" and our NeurIPS 2023 paper…☆52Updated this week
- A new framework to transform any neural networks into an interpretable concept-bottleneck-model (CBM) without needing labeled concept dat…☆79Updated 7 months ago
- This is a list of awesome prototype-based papers for explainable artificial intelligence.☆34Updated last year
- This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.☆42Updated last year
- Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations is a ServiceNow Research project that was started at Elemen…☆13Updated last year
- Pytorch SimCLR on CIFAR10 (92.85% test accuracy)☆55Updated 4 years ago
- Paper of out of distribution detection and generalization☆52Updated last year
- A curated list of papers and resources about the distribution shift in machine learning.☆104Updated last year
- [ICLR 2023 spotlight] MEDFAIR: Benchmarking Fairness for Medical Imaging☆59Updated last year
- Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)☆61Updated last year
- [CLeaR23] Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning☆29Updated last year
- Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style☆48Updated 2 years ago
- Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)☆21Updated last year
- A collection of model transferability estimation methods.☆24Updated last month
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆63Updated 5 months ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆49Updated 3 years ago
- Existing literature about training-data analysis.☆17Updated 2 years ago
- Benchmark study of quality and faithfulness of counterfactual image generation☆14Updated last week
- ☆42Updated last year
- NeurIPS 2021 | Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information☆32Updated 2 years ago
- Quantile risk minimization☆24Updated 3 months ago
- ☆65Updated 4 years ago
- We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness o…☆56Updated 2 years ago