eberharf / cfl

Related projects ⓘ

Alternatives and complementary repositories for cfl

• larslorch / dibs
  DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021
  ☆46Updated 8 months ago
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆27Updated 3 years ago
• csquires / causal-rep-learning-reading-group
  ☆21Updated last year
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆55Updated 3 years ago
• francescomontagna / causally
  Code for the causal benchmark library
  ☆10Updated last month
• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆80Updated 2 years ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆44Updated 3 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆17Updated 2 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆38Updated last year
• lgresele / independent-mechanism-analysis
  Code for the paper: "Independent mechanism analysis, a new concept?"
  ☆25Updated last year
• andrew-cr / online_var_fil
  Code for our paper: Online Variational Filtering and Parameter Learning
  ☆18Updated 2 years ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆80Updated 7 months ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 3 years ago
• fbickfordsmith / epig
  Bayesian active learning with EPIG data acquisition
  ☆25Updated 6 months ago
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆55Updated 8 months ago
• team-approx-bayes / kpriors
  Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.
  ☆16Updated 2 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆38Updated 3 months ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• juangamella / aicp
  Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…
  ☆19Updated last year
• tranbahien / you-need-a-good-prior
  All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)
  ☆21Updated 2 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆18Updated 5 years ago
• cbg-ethz / bmi
  Mutual information estimators and benchmark
  ☆37Updated 3 weeks ago
• Scriddie / Varsortability
  Implementations of var-sortability, sortnregress, and chain-orientation as presented in the article "Beware of the Simulated DAG": https:…
  ☆15Updated last year
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 4 years ago
• ermongroup / HyperSPN
  PyTorch implementation for "HyperSPNs: Compact and Expressive Probabilistic Circuits", NeurIPS 2021
  ☆13Updated 3 years ago
• PGM-Lab / 2023-ProbAI
  Repo for the Tutorials of Day1-Day2 of the Nordic Probabilistic AI School 2023
  ☆17Updated last year
• frgsimpson / kitt
  Kernel Identification Through Transformers
  ☆12Updated last year
• MFreidank / pysgmcmc
  Bayesian Deep Learning with Stochastic Gradient MCMC Methods
  ☆38Updated 3 years ago
• slachapelle / disentanglement_via_mechanism_sparsity
  ☆17Updated 10 months ago