MaheepChaudhary / Causality-in-Trustworthy-Machine-LearningLinks
The repository contains lists of papers on causality and how relevant techniques are being used to further enhance deep learning era computer vision solutions.
☆99Updated 2 years ago
Alternatives and similar repositories for Causality-in-Trustworthy-Machine-Learning
Users that are interested in Causality-in-Trustworthy-Machine-Learning are comparing it to the libraries listed below
Sorting:
- A curated list of papers and resources about the distribution shift in machine learning.☆123Updated 2 years ago
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆111Updated 2 years ago
- ☆37Updated 2 years ago
- Repository for our NeurIPS 2022 paper "Concept Embedding Models", our NeurIPS 2023 paper "Learning to Receive Help", and our ICML 2025 pa…☆69Updated last month
- Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.☆175Updated 2 years ago
- Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments☆75Updated 2 years ago
- An amortized approach for calculating local Shapley value explanations☆102Updated last year
- Official implementation for "Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition" (I…☆43Updated 2 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆51Updated 4 years ago
- Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"☆19Updated 4 years ago
- This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.☆46Updated 2 years ago
- Benchmark study of quality and faithfulness of counterfactual image generation☆29Updated 6 months ago
- ☆44Updated 2 weeks ago
- This is a list of awesome prototype-based papers for explainable artificial intelligence.☆39Updated 2 years ago
- Coresets via Bilevel Optimization☆67Updated 5 years ago
- ☆36Updated 4 years ago
- The official PyTorch implementation - Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from t…☆83Updated 3 years ago
- Concept Bottleneck Models, ICML 2020☆223Updated 2 years ago
- Code for the ICLR 2022 paper "Attention-based interpretability with Concept Transformers"☆42Updated last month
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)☆99Updated 9 months ago
- Optimal Transport Dataset Distance☆173Updated 3 years ago
- Experiments to reproduce results in Interventional Causal Representation Learning.☆26Updated 2 years ago
- ☆25Updated 3 years ago
- Survey for Distribution Shift☆19Updated 4 years ago
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"☆54Updated 3 years ago
- Existing literature about training-data analysis.☆17Updated 3 years ago
- [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization☆53Updated last year
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆36Updated last year
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆145Updated 2 years ago
- [ICLR 23] A new framework to transform any neural networks into an interpretable concept-bottleneck-model (CBM) without needing labeled c…☆120Updated last year