Alternatives and similar repositories for StructuredNNs:

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

• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆83Updated 2 years ago
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆63Updated last week
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆41Updated last year
• yannadani / cbed
  Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.
  ☆19Updated 2 years ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆44Updated 3 years ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆83Updated 10 months ago
• Harshs27 / neural-graphical-models
  Neural Graphical models are neural network based graphical models that offer richer representation, faster inference & sampling
  ☆28Updated last year
• microsoft / csuite
  CSuite: A Suite of Benchmark Datasets for Causality
  ☆64Updated last year
• lfbo-ml / lfbo
  Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022
  ☆44Updated 2 years ago
• larslorch / dibs
  DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021
  ☆47Updated 11 months ago
• akekic / causal-component-analysis
  ☆22Updated last year
• EdinburghNLP / torch-adaptive-imle
  ☆34Updated 2 months ago
• juangamella / aicp
  Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…
  ☆19Updated last year
• GFNOrg / EB_GFN
  Code for our paper "Generative Flow Networks for Discrete Probabilistic Modeling"
  ☆81Updated last year
• IDSIA / neuraldiffeq-fwp
  Official repository for the paper "Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules" (…
  ☆19Updated 2 years ago
• remilepriol / causal-adaptation-speed
  Investigate the speed of adaptation of structural causal models
  ☆16Updated 4 years ago
• lgresele / independent-mechanism-analysis
  Code for the paper: "Independent mechanism analysis, a new concept?"
  ☆24Updated last year
• lazaratan / dyn-gfn
  DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks
  ☆51Updated 11 months ago
• psanch21 / causal-flows
  ☆53Updated 6 months ago
• gcucurull / maml_flax
  Model Agnostic Meta Learning (MAML) implemented in Flax, the neural network library for JAX.
  ☆19Updated 4 years ago
• rpatrik96 / nl-causal-representations
  This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (partic…
  ☆17Updated 5 months ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆18Updated 3 years ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆42Updated 2 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆21Updated 4 years ago
• MichaelArbel / GeneralizedEBM
  ☆53Updated 6 months ago
• ermongroup / SPN_Variational_Inference
  PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020
  ☆16Updated 3 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 5 years ago
• phlippe / CITRIS
  Code repository of the paper "CITRIS: Causal Identifiability from Temporal Intervened Sequences" and "iCITRIS: Causal Representation Lear…
  ☆50Updated last year
• bhoov / energy-transformer-jax
  The Energy Transformer block, in JAX
  ☆56Updated last year