Alternatives and similar repositories for bdl-benchmarks

Users that are interested in bdl-benchmarks are comparing it to the libraries listed below

• team-approx-bayes / dl-with-bayes
  Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"
  ☆245Updated 5 years ago
• kyle-dorman / bayesian-neural-network-blogpost
  Building a Bayesian deep learning classifier
  ☆488Updated 7 years ago
• paraschopra / bayesian-neural-network-mnist
  Bayesian neural network using Pyro and PyTorch on MNIST dataset
  ☆312Updated 6 years ago
• wjmaddox / swa_gaussian
  Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"
  ☆469Updated 2 years ago
• bayesgroup / deepbayes-2019
  Practical assignments of the Deep|Bayes summer school 2019
  ☆833Updated 5 years ago
• yaringal / DropoutUncertaintyExps
  Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"
  ☆575Updated 3 years ago
• RobRomijnders / weight_uncertainty
  Implementing Bayes by Backprop
  ☆184Updated 6 years ago
• AlaaLab / deep-learning-uncertainty
  Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…
  ☆628Updated 2 years ago
• ssydasheng / Bayesian_neural_network_papers
  Papers for Bayesian-NN
  ☆325Updated 6 years ago
• google-research / robustness_metrics
  ☆470Updated 2 months ago
• google / edward2
  A simple probabilistic programming language.
  ☆699Updated 2 weeks ago
• google-deepmind / neural-processes
  This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural P…
  ☆1,005Updated 4 years ago
• ctallec / pyvarinf
  Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
  ☆359Updated 5 years ago
• probtorch / probtorch
  Probabilistic Torch is library for deep generative models that extends PyTorch
  ☆890Updated last year
• izmailovpavel / understandingbdl
  ☆241Updated 2 years ago
• kumar-shridhar / Master-Thesis-BayesianCNN
  Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
  ☆264Updated 6 years ago
• y0ast / deterministic-uncertainty-quantification
  Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"
  ☆272Updated 3 years ago
• fregu856 / papers
  I categorize, annotate and write comments for all research papers I read (460+ papers since 2018).
  ☆406Updated last month
• karpathy / pytorch-normalizing-flows
  Normalizing flows in PyTorch. Current intended use is education not production.
  ☆873Updated 5 years ago
• BlackHC / BatchBALD
  Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning.
  ☆241Updated last year
• mlss-2019 / tutorials
  ☆275Updated 5 years ago
• nitarshan / bayes-by-backprop
  PyTorch implementation of "Weight Uncertainty in Neural Networks"
  ☆176Updated 3 years ago
• joanbruna / MathsDL-spring19
  Mathematics of Deep Learning, Courant Insititute, Spring 19
  ☆277Updated 6 years ago
• google-deepmind / dsprites-dataset
  Dataset to assess the disentanglement properties of unsupervised learning methods
  ☆509Updated 4 years ago
• EmilienDupont / augmented-neural-odes
  Pytorch implementation of Augmented Neural ODEs
  ☆542Updated 2 years ago
• google / uncertainty-baselines
  High-quality implementations of standard and SOTA methods on a variety of tasks.
  ☆1,517Updated last month
• yaringal / ConcreteDropout
  Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832
  ☆251Updated 6 years ago
• pyprob / pyprob
  A probabilistic programming system for simulators and high-performance computing (HPC), based on PyTorch
  ☆390Updated last year
• baal-org / baal
  Bayesian active learning library for research and industrial usecases.
  ☆900Updated 3 weeks ago
• cpark321 / uncertainty-deep-learning
  ☆238Updated 5 years ago