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:
- Python package for evaluating model calibration in classification☆20Updated 6 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- ☆32Updated 7 years ago
- ☆43Updated 7 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆42Updated 3 years ago
- Code for the ICML 2019 paper: Distribution Calibration for Regression☆22Updated 2 years ago
- Last-layer Laplace approximation code examples☆83Updated 4 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
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆86Updated 5 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 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
- Sample code for running deterministic variational inference to train Bayesian neural networks☆101Updated 7 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 7 years ago
- SGD and Ordered SGD codes for deep learning, SVM, and logistic regression☆36Updated 5 years ago
- Code for Augment & Reduce, a scalable stochastic algorithm for large categorical distributions☆10Updated 7 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 4 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- ☆18Updated last year
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆61Updated 7 years ago
- ☆13Updated 7 years ago
- ☆63Updated 5 years ago
- ☆40Updated 6 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆63Updated 5 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 5 years ago
- Deep convolutional gaussian processes.☆83Updated 6 years ago
- PyTorch implementation of nonsymmetric determinantal point process (DPP) learning.☆25Updated 2 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
- ☆54Updated last year
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆91Updated 5 years ago