rgklab / StructuredNNs

Related projects: ⓘ

• ssokota / mec
  Code for minimum-entropy coupling.
  ☆29Updated 2 months ago
• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆78Updated 2 years ago
• AlCorreia / GeFs
  Generative Forests in Python
  ☆32Updated last year
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆35Updated last year
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆51Updated 6 months ago
• EdinburghNLP / torch-adaptive-imle
  ☆32Updated 9 months ago
• yannadani / cbed
  Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.
  ☆19Updated last year
• isgibbs / DtACI
  ☆14Updated 4 months ago
• MichaelArbel / GeneralizedEBM
  ☆52Updated last month
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆78Updated 5 months ago
• dylandoblar / noether-networks
  Meta-learning inductive biases in the form of useful conserved quantities.
  ☆37Updated last year
• arranger1044 / probabilistic-circuits
  A curated collection of papers on probabilistic circuits, computational graphs encoding tractable probability distributions.
  ☆47Updated 7 months ago
• cambridge-mlg / EinsumNetworks
  ☆50Updated last year
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆20Updated 3 years ago
• google-deepmind / enn_acme
  ☆29Updated 2 years ago
• zecevic-matej / Not-All-Causal-Inference-is-the-Same
  Official code repository to the corresponding paper.
  ☆28Updated last year
• ThomasMiconi / Meta-Task-Generator
  Automatically generate simple meta-learning tasks from a very large space
  ☆15Updated last year
• phlippe / CITRIS
  Code repository of the paper "CITRIS: Causal Identifiability from Temporal Intervened Sequences" and "iCITRIS: Causal Representation Lear…
  ☆47Updated last year
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 2 years ago
• microsoft / csuite
  CSuite: A Suite of Benchmark Datasets for Causality
  ☆55Updated last year
• ericmjl / score-models
  In which I learn about score functions and how they can be used to generate data.
  ☆14Updated 5 months ago
• april-tools / gekcs
  How to Turn Your Knowledge Graph Embeddings into Generative Models
  ☆40Updated 2 months ago
• Harshs27 / neural-graphical-models
  Neural Graphical models are neural network based graphical models that offer richer representation, faster inference & sampling
  ☆24Updated 10 months ago
• neildhir / DCBO
  Dynamic causal Bayesian optimisation
  ☆32Updated last year
• ml-jku / DIffUCO
  ☆26Updated last week
• microsoft / goodpoints
  A Python package for generating concise, high-quality summaries of a probability distribution
  ☆39Updated 3 months ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• lgresele / independent-mechanism-analysis
  Code for the paper: "Independent mechanism analysis, a new concept?"
  ☆25Updated last year
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆17Updated 2 years ago
• gengala / egnca
  Official implementation of E(n)-equivariant Graph Neural Cellular Automata
  ☆22Updated 4 months ago