bmucsanyi / untangle
Large-scale uncertainty benchmark in deep learning.
☆55Updated 2 months ago
Alternatives and similar repositories for untangle:
Users that are interested in untangle are comparing it to the libraries listed below
- ☆17Updated 7 months ago
- Bayesian active learning with EPIG data acquisition☆31Updated last week
- A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…☆52Updated last year
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆66Updated 5 months ago
- Simple (and cheap!) neural network uncertainty estimation☆63Updated last week
- ☆18Updated last year
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆129Updated 2 years ago
- Instructions and examples to deploy some PyTorch code on slurm using a Singularity Container☆33Updated 2 years ago
- Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024☆28Updated 7 months ago
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆36Updated last month
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆66Updated 2 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆43Updated 2 years ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆35Updated 2 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆112Updated 2 years ago
- ☆32Updated 2 years ago
- Official implementation of "How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?", TMLR 2023.☆18Updated last year
- Code of the paper "Beyond calibration: estimating the grouping loss of modern neural networks" published in ICLR 2023.☆12Updated last year
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 11 months ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Code for experiments to learn uncertainty☆30Updated 2 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆76Updated 2 years ago
- ☆25Updated last year
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated last year
- Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"☆40Updated 2 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆139Updated last year
- Agustinus' very opiniated publication-ready plotting library☆63Updated 2 months ago
- ☆146Updated last year
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- A library for uncertainty quantification based on PyTorch☆123Updated 3 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago