Alternatives and similar repositories for natural-posterior-network

Users that are interested in natural-posterior-network are comparing it to the libraries listed below

• sharpenb / Posterior-Network
  Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)
  ☆78Updated 3 years ago
• y0ast / DUE
  Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".
  ☆113Updated 3 years ago
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆76Updated last year
• MJ10 / DEUP
  Code for experiments to learn uncertainty
  ☆30Updated 2 years ago
• pasteurlabs / unreasonable_effective_der
  Supplementary material to reproduce "The Unreasonable Effectiveness of Deep Evidential Regression"
  ☆28Updated 2 years ago
• Jiacheng-Zhu-AIML / WGPOT
  The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
  ☆53Updated 5 years ago
• FrederikWarburg / LaplaceAE
  ☆32Updated 3 years ago
• JanRocketMan / regression-prior-networks
  An official PyTorch implementation of "Regression Prior Networks" for effective runtime uncertainty estimation.
  ☆36Updated 4 years ago
• giannifranchi / LP_BNN
  This repository contains an official implementation of LPBNN.
  ☆38Updated 2 years ago
• dngfra / repulsive_ensembles
  Repo for our paper "Repulsive deep ensembles are Bayesian"
  ☆19Updated 3 years ago
• saleml / continuous-gfn
  ☆27Updated 2 years ago
• ngruver / lie-deriv
  ☆38Updated 2 years ago
• chingyaoc / kV-Margin
  NeurIPS 2021, Code for Measuring Generalization with Optimal Transport
  ☆28Updated 3 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 4 years ago
• yliess86 / BayeFormers
  General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…
  ☆45Updated 4 years ago
• avitase / mder
  Supplementary material to reproduce "Multivariate Deep Evidential Regression"
  ☆20Updated 3 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆42Updated 3 months ago
• orientino / dum-components
  Code for "Training, Architecture, and Prior for Deterministic Uncertainty Methods" ICLR 2023 Workshop on Trustworthy ML
  ☆12Updated 2 years ago
• TorchUQ / torchuq
  A library for uncertainty quantification based on PyTorch
  ☆122Updated 3 years ago
• martius-lab / beta-nll
  beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022
  ☆46Updated 3 years ago
• y0ast / deterministic-uncertainty-quantification
  Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"
  ☆272Updated 3 years ago
• tjoo512 / belief-matching-framework
  Belief matching framework official implementation
  ☆40Updated 2 years ago
• DLR-RM / curvature
  Official Code: Estimating Model Uncertainty of Neural Networks in Sparse Information Form, ICML2020.
  ☆31Updated 4 years ago
• volagold / nce
  Noise Contrastive Estimation (NCE) in PyTorch
  ☆32Updated 6 months ago
• ifiaposto / Distance_Aware_Bottleneck
  Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024
  ☆28Updated last year
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• SaynaEbrahimi / UCB
  Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020
  ☆75Updated 4 years ago
• lfbo-ml / lfbo
  Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022
  ☆44Updated 3 years ago