Alternatives and similar repositories for csm:

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

• rfeinman / learning-to-learn
  Code for "Learning Inductive Biases with Simple Neural Networks" (Feinman & Lake, 2018).
  ☆22Updated 6 years ago
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆31Updated 3 years ago
• rfeinman / pyBPL
  Python implementation of Bayesian Program Learning tools (with PyTorch)
  ☆71Updated 2 years ago
• OATML / ucate
  Uncertainty in Conditional Average Treatment Effect Estimation
  ☆31Updated 4 years ago
• franrruiz / uivi
  Code for Unbiased Implicit Variational Inference (UIVI)
  ☆14Updated 6 years ago
• hanyas / mimo
  A toolbox for inference of mixture models
  ☆16Updated last year
• OATML / causal-bald
  ☆17Updated last year
• csquires / causal-rep-learning-reading-group
  ☆22Updated last year
• nke001 / causal_learning_unknown_interventions
  Code for "Neural causal learning from unknown interventions"
  ☆101Updated 4 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆19Updated 3 years ago
• thegregyang / NNspectra
  Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube
  ☆47Updated 5 years ago
• facebookresearch / productive_concept_learning
  Code for the benchmark containing dataset, models and metrics for productive concept learning -- a kind of compositional reasoning task t…
  ☆17Updated 3 years ago
• djsutherland / igms
  Implicit generative models and related stuff based on the MMD, in PyTorch
  ☆16Updated 4 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 6 years ago
• nikikilbertus / general-iv-models
  Bounding causal effects in general (continuous, non-additive) instrumental variable models.
  ☆14Updated last year
• lopezpaz / causation_learning_theory
  Code for "Towards a learning theory of cause-effect inference" (ICML 2015).
  ☆29Updated 4 years ago
• enalisnick / paper_summaries
  Summaries and minimal implementations of ML / statistics research articles.
  ☆39Updated 4 years ago
• hardmaru / mdn_jax_tutorial
  Mixture Density Networks (Bishop, 1994) tutorial in JAX
  ☆59Updated 4 years ago
• CalculatedContent / ImplicitSelfRegularization
  Repo to accompany paper "Implicit Self-Regularization in Deep Neural Networks..."
  ☆43Updated 6 years ago
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆22Updated 2 years ago
• oxcsml / ML_bazaar
  OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.
  ☆93Updated 3 years ago
• joelouismarino / iterative_inference
  Implementation of iterative inference in deep latent variable models
  ☆43Updated 5 years ago
• rgiordan / vittles
  "Variational inference tools to leverage estimator sensitivity."
  ☆16Updated last year
• geyang / plan2vec
  Public Release of Plan2vec Implementation in pyTorch
  ☆56Updated 2 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 5 years ago
• tbrx / compiled-inference
  Train neural networks to use as SMC and importance sampling proposals
  ☆24Updated 7 years ago
• rrtucci / JudeasRx
  python app for doing personalized causal medicine using the methods invented by Judea Pearl et al.
  ☆25Updated 2 years ago
• pyro-ppl / sandbox
  Pyro models and misc examples.
  ☆19Updated 3 years ago
• joelouismarino / variational_rl
  Variational Reinforcement Learning
  ☆16Updated 8 months ago