microsoft / otdd
Optimal Transport Dataset Distance
☆163Updated 2 years ago
Alternatives and similar repositories for otdd:
Users that are interested in otdd are comparing it to the libraries listed below
- Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments☆73Updated 2 years ago
- This repository contains the code of the distribution shift framework presented in A Fine-Grained Analysis on Distribution Shift (Wiles e…☆83Updated last month
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆139Updated last year
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆107Updated last year
- A benchmark for distribution shift in tabular data☆52Updated 10 months ago
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆66Updated 2 years ago
- Code for the intrinsic dimensionality estimate of data representations☆80Updated 5 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆148Updated 2 years ago
- Model Zoos published at the NeurIPS 2022 Dataset & Benchmark track: "Model Zoos: A Dataset of Diverse Populations of Neural Network Model…☆54Updated last year
- A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.☆563Updated last year
- Framework code with wandb, checkpointing, logging, configs, experimental protocols. Useful for fine-tuning models or training from scratc…☆150Updated 2 years ago
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)☆95Updated 2 months ago
- Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.☆176Updated last year
- A curated list of papers and resources about the distribution shift in machine learning.☆115Updated last year
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆112Updated 2 years ago
- Code for the ICLR 2022 paper. Salient Imagenet: How to discover spurious features in deep learning?☆40Updated 2 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆121Updated 3 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆160Updated last year
- Reusable BatchBALD implementation☆79Updated last year
- Training and evaluating NBM and SPAM for interpretable machine learning.☆77Updated 2 years ago
- ☆107Updated last year
- Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"☆40Updated 2 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆76Updated 2 years ago
- A simple PyTorch implementation of influence functions.☆85Updated 10 months ago
- NumPy library for calibration metrics☆69Updated last month
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 11 months ago
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 3 years ago
- ☆45Updated 2 years ago
- Code release for REPAIR: REnormalizing Permuted Activations for Interpolation Repair☆47Updated last year
- Project site for "Your Classifier is Secretly an Energy-Based Model and You Should Treat it Like One"☆422Updated 2 years ago