p-lambda / verified_calibrationLinks
Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlight).
☆150Updated 2 years ago
Alternatives and similar repositories for verified_calibration
Users that are interested in verified_calibration are comparing it to the libraries listed below
Sorting:
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆244Updated 2 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆160Updated last year
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- Calibration of Convolutional Neural Networks☆168Updated 2 years ago
- Reusable BatchBALD implementation☆79Updated last year
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆112Updated 3 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated last year
- Reliability diagrams visualize whether a classifier model needs calibration☆154Updated 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 …☆364Updated last year
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated last year
- Tools for training explainable models using attribution priors.☆124Updated 4 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆470Updated 2 years ago
- NumPy library for calibration metrics☆73Updated 5 months ago
- ☆241Updated 2 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆245Updated 5 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆128Updated 4 years ago
- Last-layer Laplace approximation code examples☆82Updated 3 years ago
- Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119…☆105Updated last year
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆54Updated 2 years ago
- A benchmark for distribution shift in tabular data☆55Updated last year
- ☆470Updated 3 months ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- Combating hidden stratification with GEORGE☆64Updated 4 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆131Updated 4 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆143Updated 2 years ago
- ☆124Updated 4 years ago
- Optimal Transport Dataset Distance☆168Updated 3 years ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Updated 2 years ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆130Updated 2 years ago
- Large-scale uncertainty benchmark in deep learning.☆61Updated 2 months ago