izmailovpavel / neurips_bdl_starter_kit

Related projects ⓘ

Alternatives and complementary repositories for neurips_bdl_starter_kit

• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆86Updated 5 months ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆18Updated 5 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 4 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆37Updated last year
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆55Updated 3 years ago
• fbickfordsmith / epig
  Bayesian active learning with EPIG data acquisition
  ☆25Updated 5 months ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆72Updated last year
• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆44Updated 3 years ago
• Sanaelotfi / Bayesian_model_comparison
  Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".
  ☆35Updated 2 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆68Updated last year
• MichaelArbel / GeneralizedEBM
  ☆52Updated 3 months ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆80Updated 4 months ago
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 4 years ago
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆9Updated 2 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 4 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 3 years ago
• PGM-Lab / probai-2021-pyro
  Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)
  ☆47Updated 3 years ago
• g-benton / loss-surface-simplexes
  ☆97Updated 2 years ago
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆43Updated last year
• MachineLearningLifeScience / stochman
  Algorithms for computations on random manifolds made easier
  ☆85Updated 11 months ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆17Updated 2 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆80Updated 4 years ago
• aangelopoulos / ltt
  Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
  ☆63Updated 5 months ago
• iffsid / DReG-PyTorch
  A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"
  ☆18Updated 5 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆77Updated 3 years ago
• y0ast / DUE
  Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".
  ☆111Updated 2 years ago
• YannDubs / Invariant-Self-Supervised-Learning
  Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"
  ☆40Updated last year
• f-dangel / curvlinops
  scipy linear operators for the Hessian, Fisher/GGN, and more in PyTorch
  ☆17Updated this week
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆86Updated 4 years ago