Alternatives and similar repositories for DeeplyUncertain-Public

Users that are interested in DeeplyUncertain-Public are comparing it to the libraries listed below

• bccp / DeepUQ
  Bayesian Uncertainty Quantification by Deep Generative Model
  ☆19Updated 5 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• ireis / PRF
  Probabilistic Random Forest: A machine learning algorithm for noisy datasets
  ☆129Updated last year
• florent-leclercq / Bayes_InfoTheory
  Lectures on Bayesian statistics and information theory
  ☆31Updated 4 months ago
• mvaldenegro / keras-uncertainty
  Utilities to perform Uncertainty Quantification on Keras Models
  ☆119Updated last year
• sbi-dev / pyknos
  Conditional density estimation with neural networks
  ☆33Updated 8 months ago
• jfcrenshaw / pzflow
  Probabilistic modeling of tabular data with normalizing flows.
  ☆58Updated 2 weeks ago
• TyXe-BDL / TyXe
  ☆154Updated 3 years ago
• dflemin3 / approxposterior
  A Python package for approximate Bayesian inference and optimization using Gaussian processes
  ☆42Updated last year
• blt2114 / CDE_with_BNF
  Toy Examples of Conditional Density Estimation with Bayesian Normalizing flows
  ☆22Updated 7 years ago
• DanieleGammelli / pyro-torch-normalizing-flows
  Implementations of Normalizing Flows in Pytorch/Pyro
  ☆18Updated 5 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated 11 months ago
• probabilists / lampe
  Likelihood-free AMortized Posterior Estimation with PyTorch
  ☆131Updated last year
• justinalsing / pydelfi
  Density Estimation Likelihood-Free Inference with neural density estimators and adaptive acquisition of simulations
  ☆110Updated 2 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆89Updated 5 years ago
• vistalab-technion / vqr
  Vector Quantile Regression
  ☆19Updated 6 months ago
• Goobley / Radynversion
  Inverting Solar Flare Observations with Invertible Neural Nets (with RADYN physics)
  ☆13Updated 4 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• AaltoML / spatio-temporal-GPs
  Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'
  ☆47Updated 3 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 4 years ago
• mfouesneau / NUTS
  python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011
  ☆132Updated 4 years ago
• undark-lab / swyft
  A system for scientific simulation-based inference at scale.
  ☆164Updated last year
• biweidai / SINF
  Sliced Iterative Generator (SIG) & Gaussianizing Iterative Slicing (GIS)
  ☆37Updated 2 years ago
• mackelab / simformer
  Combination of transformers and diffusion models for flexible all-in-one simulation-based inference
  ☆71Updated 3 months ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 3 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated last year
• smsharma / sbi-lecture-mit
  Notebook to go along with a lecture for the MIT course 8.16: Data Science in Physics on neural simulation-based inference.
  ☆58Updated last year
• alpha-davidson / TensorBNN
  Full Bayesian inference for neural networks using TensorFlow
  ☆15Updated 4 years ago
• montefiore-institute / balanced-nre
  Code for the paper "Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation".
  ☆14Updated 2 years ago
• PredictiveScienceLab / uq-course
  Introduction to Uncertainty Quantification
  ☆255Updated 3 years ago