p-lambda / wilds
A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.
☆564Updated last year
Alternatives and similar repositories for wilds:
Users that are interested in wilds are comparing it to the libraries listed below
- PyTorch code to run synthetic experiments.☆421Updated 3 years ago
- Distributionally robust neural networks for group shifts☆262Updated 2 years ago
- An implementation of the BADGE batch active learning algorithm.☆206Updated 11 months ago
- Project site for "Your Classifier is Secretly an Energy-Based Model and You Should Treat it Like One"☆423Updated 2 years ago
- ☆469Updated this week
- Optimal Transport Dataset Distance☆164Updated 2 years ago
- Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using co…☆330Updated last year
- ☆410Updated 3 years ago
- This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence…☆333Updated last year
- Reliability diagrams visualize whether a classifier model needs calibration☆150Updated 3 years ago
- Implementation of Estimating Training Data Influence by Tracing Gradient Descent (NeurIPS 2020)☆230Updated 3 years ago
- Concept Bottleneck Models, ICML 2020☆200Updated 2 years ago
- A clean and simple data loading library for Continual Learning☆429Updated last year
- Benchmark your model on out-of-distribution datasets with carefully collected human comparison data (NeurIPS 2021 Oral)☆347Updated 2 weeks ago
- Code for coreset selection methods☆232Updated 2 years ago
- Code for the paper "A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks".☆345Updated 5 years ago
- A Pytorch-Lightning implementation of self-supervised algorithms☆538Updated 3 years ago
- 👽 Out-of-Distribution Detection with PyTorch☆289Updated this week
- ☆325Updated 2 weeks ago
- ImageNet-R(endition) and DeepAugment (ICCV 2021)☆264Updated 3 years ago
- Mode Connectivity and Fast Geometric Ensembles in PyTorch☆270Updated 2 years ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆239Updated 2 years ago
- Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020☆235Updated 2 years ago
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆624Updated 2 years ago
- 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☆108Updated last year
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated last year
- Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.☆176Updated last year
- Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels☆295Updated last year
- A simple way to calibrate your neural network.☆1,144Updated 3 years ago