JonathanWenger / pycalibLinks
Non-Parametric Calibration for Classification (AISTATS 2020)
☆19Updated 3 years ago
Alternatives and similar repositories for pycalib
Users that are interested in pycalib are comparing it to the libraries listed below
Sorting:
- ☆43Updated 7 years ago
- Python package for evaluating model calibration in classification☆20Updated 6 years ago
- ☆32Updated 7 years ago
- Code for the ICML 2019 paper: Distribution Calibration for Regression☆22Updated 2 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- SGD and Ordered SGD codes for deep learning, SVM, and logistic regression☆36Updated 5 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆43Updated 4 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆151Updated 3 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆28Updated 4 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 4 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆43Updated 2 years ago
- Last-layer Laplace approximation code examples☆83Updated 4 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- Code for our ICLR19 paper "Wasserstein Barycenters for Model Ensembling", Pierre Dognin, Igor Melnyk, Youssef Mroueh, Jarret Ross, Cicero…☆23Updated 6 years ago
- ☆63Updated 5 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 3 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 5 years ago
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Updated 2 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 7 years ago
- A Python implementation of Kernel Mean Matching data reweighting algorithm☆33Updated 10 years ago
- ☆83Updated 2 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆42Updated 3 years ago
- Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AA…☆76Updated 8 years ago
- Code for Sliced Gromov-Wasserstein☆69Updated 6 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- ☆21Updated 3 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- This repository contains the code used in a publication 'Active Learning for Decision-Making from Imbalanced Observational Data', Iiris S…☆11Updated 6 years ago