p-lambda / wildsLinks
A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.
☆565Updated last year
Alternatives and similar repositories for wilds
Users that are interested in wilds are comparing it to the libraries listed below
Sorting:
- ☆470Updated last month
- PyTorch code to run synthetic experiments.☆422Updated 3 years ago
- Distributionally robust neural networks for group shifts☆265Updated 2 years ago
- Project site for "Your Classifier is Secretly an Energy-Based Model and You Should Treat it Like One"☆423Updated 2 years ago
- An implementation of the BADGE batch active learning algorithm.☆205Updated 11 months ago
- Domain adaptation made easy. Fully featured, modular, and customizable.☆375Updated 2 years ago
- A clean and simple data loading library for Continual Learning☆430Updated last year
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆363Updated 9 months ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated last year
- Optimal Transport Dataset Distance☆164Updated 3 years ago
- 👽 Out-of-Distribution Detection with PyTorch☆293Updated 3 weeks ago
- Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020☆235Updated 2 years ago
- DISTIL: Deep dIverSified inTeractIve Learning. An active/inter-active learning library built on py-torch for reducing labeling costs.☆150Updated 2 years ago
- Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments☆74Updated 2 years ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,511Updated last month
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆141Updated 2 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- ☆412Updated 3 years ago
- Implementation of Estimating Training Data Influence by Tracing Gradient Descent (NeurIPS 2020)☆231Updated 3 years ago
- Awesome Active Learning Paper List☆141Updated last year
- 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 2 years ago
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆108Updated last year
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆472Updated last year
- A simple way to calibrate your neural network.☆1,147Updated 3 years ago
- Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels☆295Updated 2 years ago
- This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence…☆333Updated last year
- This code package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpreta…☆365Updated 3 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆150Updated 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…☆241Updated 2 years ago
- Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.☆176Updated last year