Alternatives and similar repositories for simple-einet

Users that are interested in simple-einet are comparing it to the libraries listed below

• AlCorreia / cm-tpm
  Code in support of the paper Continuous Mixtures of Tractable Probabilistic Models
  ☆11Updated 9 months ago
• ermongroup / HyperSPN
  PyTorch implementation for "HyperSPNs: Compact and Expressive Probabilistic Circuits", NeurIPS 2021
  ☆13Updated 3 years ago
• april-tools / cirkit
  a python framework to build, learn and reason about probabilistic circuits and tensor networks
  ☆115Updated 3 weeks ago
• cambridge-mlg / EinsumNetworks
  ☆52Updated last year
• 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
• HEmile / storchastic
  Stochastic Automatic Differentiation library for PyTorch.
  ☆205Updated 11 months ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆77Updated 4 years ago
• deeprob-org / deeprob-kit
  A Python Library for Deep Probabilistic Modeling
  ☆61Updated 9 months ago
• Tractables / pyjuice
  Scalable training and inference for Probabilistic Circuits
  ☆70Updated 3 weeks ago
• UCLA-StarAI / Density-Estimation-Datasets
  A collection of commonly used datasets as benchmarks for density estimation
  ☆24Updated 5 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• MachineLearningLifeScience / stochman
  Algorithms for computations on random manifolds made easier
  ☆91Updated last year
• andres-fr / skerch
  Sketched matrix decompositions for PyTorch
  ☆70Updated this week
• april-tools / squared-npcs
  Squared Non-monotonic Probabilistic Circuits
  ☆22Updated 6 months ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆20Updated 3 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• JTT94 / filterflow
  Extensible Tensorflow library for differentiable particle filtering. ICML 2021.
  ☆42Updated 2 years ago
• KareemYousrii / SPL
  This repository holds the code for the NeurIPS 2022 paper, Semantic Probabilistic Layers
  ☆30Updated last year
• arranger1044 / DEBD
  A collection of commonly used datasets as benchmarks for density estimation in MaLe
  ☆19Updated 6 years ago
• TrentBrick / PyTorchDiscreteFlows
  Discrete Normalizing Flows implemented in PyTorch
  ☆114Updated 3 years ago
• lgresele / independent-mechanism-analysis
  Code for the paper: "Independent mechanism analysis, a new concept?"
  ☆24Updated 2 years ago
• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆87Updated 3 years ago
• jrmcornish / cif
  PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows
  ☆31Updated 3 years ago
• f-dangel / phd-thesis
  Source code for my PhD thesis: Backpropagation Beyond the Gradient
  ☆20Updated 2 years ago
• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆75Updated last year
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆57Updated 4 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year