Alternatives and similar repositories for pylon:

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

• pietrobarbiero / pytorch_explain
  PyTorch Explain: Interpretable Deep Learning in Python.
  ☆154Updated 11 months ago
• arranger1044 / probabilistic-circuits
  A curated collection of papers on probabilistic circuits, computational graphs encoding tractable probability distributions.
  ☆50Updated last year
• rfeinman / pyBPL
  Python implementation of Bayesian Program Learning tools (with PyTorch)
  ☆72Updated 2 years ago
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆216Updated 6 months ago
• mtensor / rulesynthesis
  Code for "Learning Compositional Rules via Neural Program Synthesis"
  ☆60Updated 4 years ago
• uclnlp / torch-imle
  Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions
  ☆258Updated last year
• tommasocarraro / LTNtorch
  PyTorch implementation of Logic Tensor Networks, a Neural-Symbolic framework.
  ☆111Updated 7 months ago
• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆87Updated 3 years ago
• debmandal / RL-Causality
  References at the Intersection of Causality and Reinforcement Learning
  ☆89Updated 4 years ago
• gblackout / NLIL
  Neural Logic Inductive Learning
  ☆42Updated 2 years ago
• KareemYousrii / SPL
  This repository holds the code for the NeurIPS 2022 paper, Semantic Probabilistic Layers
  ☆27Updated last year
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆131Updated 4 years ago
• stefanoteso / awesome-explanatory-supervision
  List of relevant resources for machine learning from explanatory supervision
  ☆157Updated 3 months ago
• AlCorreia / GeFs
  Generative Forests in Python
  ☆36Updated last year
• authors-1901-10912 / A-Meta-Transfer-Objective-For-Learning-To-Disentangle-Causal-Mechanisms
  Code for "A Meta Transfer Objective For Learning To Disentangle Causal Mechanisms"
  ☆127Updated 6 years ago
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆62Updated 3 months ago
• HEmile / storchastic
  Stochastic Automatic Differentiation library for PyTorch.
  ☆204Updated 8 months ago
• JmlrOrg / jmlr-style-file
  LaTeX style file for the Journal of Machine Learning Research
  ☆131Updated 9 months ago
• hadijomaa / dataset2vec
  ☆32Updated 3 years ago
• bradyneal / realcause
  Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…
  ☆74Updated 4 years ago
• Felix-Petersen / diffsort
  Differentiable Sorting Networks
  ☆114Updated last year
• Felix-Petersen / algovision
  Differentiable Algorithms and Algorithmic Supervision.
  ☆115Updated last year
• EdinburghNLP / torch-adaptive-imle
  ☆34Updated 5 months ago
• aangelopoulos / rcps
  Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"
  ☆86Updated last year
• uclnlp / ctp
  Conditional Theorem Proving
  ☆53Updated 4 years ago
• cambridge-mlg / EinsumNetworks
  ☆52Updated last year
• charmlab / mace
  Model Agnostic Counterfactual Explanations
  ☆87Updated 2 years ago
• stefanoteso / caipi
  CAIPI turns LIMEs into trust!
  ☆12Updated 4 years ago
• nke001 / causal_learning_unknown_interventions
  Code for "Neural causal learning from unknown interventions"
  ☆101Updated 4 years ago
• google / neural-logic-machines
  Implementation for the Neural Logic Machines (NLM).
  ☆283Updated 5 years ago