p-lambda / wildsLinks
A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.
☆592Updated 2 years ago
Alternatives and similar repositories for wilds
Users that are interested in wilds are comparing it to the libraries listed below
Sorting:
- ☆472Updated last week
- PyTorch code to run synthetic experiments.☆433Updated 4 years ago
- An implementation of the BADGE batch active learning algorithm.☆211Updated last year
- Distributionally robust neural networks for group shifts☆293Updated 3 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…☆345Updated 2 years ago
- Optimal Transport Dataset Distance☆174Updated 3 years ago
- Project site for "Your Classifier is Secretly an Energy-Based Model and You Should Treat it Like One"☆430Updated 3 years ago
- This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence…☆343Updated 2 years ago
- Implementation of Estimating Training Data Influence by Tracing Gradient Descent (NeurIPS 2020)☆239Updated 3 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆153Updated 3 years ago
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆372Updated 3 weeks ago
- A simple way to calibrate your neural network.☆1,169Updated 6 months ago
- Original dataset release for CIFAR-10H☆82Updated 5 years ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆255Updated 3 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆478Updated 2 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated 2 years ago
- A clean and simple data loading library for Continual Learning☆445Updated 2 years ago
- Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.☆175Updated 2 years ago
- Concept Bottleneck Models, ICML 2020☆239Updated 2 years ago
- Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments☆77Updated 3 years ago
- NumPy library for calibration metrics☆75Updated 3 weeks ago
- Reliability diagrams visualize whether a classifier model needs calibration☆165Updated 3 years ago
- This code package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpreta…☆388Updated 3 years ago
- ☆429Updated 4 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆275Updated 3 years ago
- ☆341Updated 6 months ago
- ☆113Updated 3 years ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,565Updated this week
- DISTIL: Deep dIverSified inTeractIve Learning. An active/inter-active learning library built on py-torch for reducing labeling costs.☆155Updated 3 years ago
- PyTorch implementation of SimCLR: supports multi-GPU training and closely reproduces results☆211Updated last year