Alternatives and similar repositories for cm-tpm

Users that are interested in cm-tpm are comparing it to the libraries listed below

• cambridge-mlg / EinsumNetworks
  ☆53Updated 2 years ago
• braun-steven / simple-einet
  An implementation of EinsumNetworks in PyTorch.
  ☆23Updated 8 months ago
• ermongroup / SPN_Variational_Inference
  PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020
  ☆17Updated 4 years ago
• cambridge-mlg / RAT-SPN
  Code for UAI'19: Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning
  ☆37Updated 5 years ago
• arranger1044 / DEBD
  A collection of commonly used datasets as benchmarks for density estimation in MaLe
  ☆20Updated 6 years ago
• dimarkov / bmr4pml
  Bayesian model reduction for probabilistic machine learning
  ☆11Updated 6 months ago
• UCLA-StarAI / Density-Estimation-Datasets
  A collection of commonly used datasets as benchmarks for density estimation
  ☆24Updated 6 years ago
• KareemYousrii / SPL
  This repository holds the code for the NeurIPS 2022 paper, Semantic Probabilistic Layers
  ☆30Updated 2 years ago
• april-tools / cirkit
  a python framework to build, learn and reason about probabilistic circuits and tensor networks
  ☆131Updated last month
• ermongroup / HyperSPN
  PyTorch implementation for "HyperSPNs: Compact and Expressive Probabilistic Circuits", NeurIPS 2021
  ☆13Updated 4 years ago
• deeprob-org / deeprob-kit
  A Python Library for Deep Probabilistic Modeling
  ☆62Updated last year
• fzaiser / nonparametric-hmc
  Implementation of Nonparametric Hamiltonian Monte Carlo
  ☆13Updated 2 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• art-ai / pypsdd
  The Python PSDD Package
  ☆19Updated 6 months ago
• arranger1044 / probabilistic-circuits
  A curated collection of papers on probabilistic circuits, computational graphs encoding tractable probability distributions.
  ☆51Updated last year
• nec-research / tf-imle
  Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation
  ☆67Updated 3 years ago
• KarenUllrich / binary-VAE
  A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.
  ☆22Updated 5 years ago
• HEmile / storchastic
  Stochastic Automatic Differentiation library for PyTorch.
  ☆208Updated last year
• AlCorreia / GeFs
  Generative Forests in Python
  ☆35Updated 2 years ago
• aboustati / vargrad
  Code accompanying VarGrad: A Low-Variance Gradient Estimator for Variational Inference
  ☆12Updated 5 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆21Updated 4 years ago
• LaurenceA / bayesfunc
  ☆15Updated 3 years ago
• HEmile / a-nesi
  A Scalable Approximate Method for Probabilistic Neurosymbolic Inference
  ☆23Updated 11 months ago
• akbir / deq-jax
  [NeurIPS'19] Deep Equilibrium Models Jax Implementation
  ☆42Updated 5 years ago
• EleMisi / VAEL
  Codebase for VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming
  ☆23Updated 2 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆54Updated 5 years ago
• gwgundersen / rflvm
  Random feature latent variable models in Python
  ☆23Updated 2 years ago
• deep-spin / sparse_continuous_distributions
  This repository provides open-source code for sparse continuous distributions and corresponding Fenchel-Young losses.
  ☆16Updated 2 years ago
• team-approx-bayes / kpriors
  Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.
  ☆16Updated 3 years ago
• agadetsky / pytorch-pl-variance-reduction
  [AAAI 2020 Oral] Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution
  ☆39Updated 5 years ago