Alternatives and similar repositories for UMNN:

Users that are interested in UMNN are comparing it to the libraries listed below

• gpapamak / maf
  Masked Autoregressive Flow
  ☆209Updated 6 months ago
• cfinlay / ffjord-rnode
  Regularized Neural ODEs (RNODE)
  ☆82Updated 3 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆81Updated 4 years ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆47Updated 4 years ago
• mbilos / neural-flows-experiments
  Experiments for Neural Flows paper
  ☆93Updated 3 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆70Updated 2 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆169Updated 3 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆56Updated 3 years ago
• cambridge-mlg / convcnp
  Implementation of the Convolutional Conditional Neural Process
  ☆121Updated 3 years ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆97Updated 10 months ago
• DartML / Stein-Variational-Gradient-Descent
  code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
  ☆98Updated 5 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• tonyduan / normalizing-flows
  Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.
  ☆273Updated last year
• 000Justin000 / torchdiffeq
  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
  ☆58Updated 4 years ago
• johannbrehmer / manifold-flow
  Manifold-learning flows (ℳ-flows)
  ☆229Updated 4 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆88Updated 4 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆109Updated 3 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆81Updated 8 months ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆44Updated 2 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆85Updated 2 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 5 years ago
• AWehenkel / Graphical-Normalizing-Flows
  Combining smooth constraint for building DAG with normalizing flow in order to replace autoregressive transformations while keeping tract…
  ☆45Updated last year
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆211Updated 8 months ago
• TrentBrick / PyTorchDiscreteFlows
  Discrete Normalizing Flows implemented in PyTorch
  ☆109Updated 3 years ago
• ex4sperans / variational-inference-with-normalizing-flows
  Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
  ☆231Updated 6 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• benrhodes26 / tre_code
  ☆23Updated 3 years ago
• facebookresearch / SingleModelUncertainty
  Learning error bars for neural network predictions
  ☆69Updated 5 years ago
• brain-research / nngp
  Deep neural network kernel for Gaussian process
  ☆203Updated 4 years ago