huckiyang / awesome-deep-causal-learning

Related projects ⓘ

Alternatives and complementary repositories for awesome-deep-causal-learning

• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• AMLab-Amsterdam / DataAugmentationInterventions
  ☆27Updated 4 years ago
• mrojascarulla / causal_transfer_learning
  ☆30Updated 6 years ago
• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆28Updated 4 years ago
• googleinterns / local_global_ts_representation
  ☆22Updated 2 years ago
• trevor-richardson / MCFlow
  Monte Carlo Flow Models for Data Imputation
  ☆17Updated 4 years ago
• cianeastwood / qrm
  Quantile risk minimization
  ☆24Updated 3 months ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 2 years ago
• jc-audet / WOODS
  Benchmarks for Out-of-Distribution Generalization in Time Series Tasks
  ☆65Updated 2 years ago
• TUM-DAML / dbu-robustness
  Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)
  ☆27Updated last year
• lmz123321 / which_invariance
  Official implementation for ICML23 paper: Which Invariance Should We Transfer? A Causal Minimax Learning Approach
  ☆11Updated 5 months ago
• jjaacckkyy63 / Causal-Intervention-AE-wAdvImg
  ☆11Updated 3 years ago
• henrikmarklund / arm
  ☆82Updated 11 months ago
• phlippe / CITRIS
  Code repository of the paper "CITRIS: Causal Identifiability from Temporal Intervened Sequences" and "iCITRIS: Causal Representation Lear…
  ☆48Updated last year
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆27Updated 3 years ago
• ioanabica / Invariant-Causal-Imitation-Learning
  Code for NeurIPS 2021 paper: "Invariant Causal Imitation Learning for Generalizable Policies" by I. Bica, D. Jarrett, M. van der Schaar
  ☆26Updated 2 years ago
• changliu00 / causal-semantic-generative-model
  Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution …
  ☆73Updated 2 years ago
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆34Updated 2 years ago
• rehg-lab / CLRec
  Pytorch implementation for "The Surprising Positive Knowledge Transfer in Continual 3D Object Shape Reconstruction"
  ☆33Updated 2 years ago
• yaohungt / Pointwise_Dependency_Neural_Estimation
  ☆19Updated 4 years ago
• google-deepmind / ssl_hsic
  ☆35Updated 3 months ago
• shwinshaker / LipGrow
  An adaptive training algorithm for residual network
  ☆14Updated 4 years ago
• mandt-lab / variational-beam-search
  Code repository of NeurIPS 2021 paper: Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning.
  ☆11Updated 2 years ago
• remilepriol / causal-adaptation-speed
  Investigate the speed of adaptation of structural causal models
  ☆16Updated 3 years ago
• HazyResearch / augmentation_code
  Reproducible code for Augmentation paper
  ☆18Updated 5 years ago
• jiaqima / SODEN
  SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks
  ☆13Updated last year
• zackchase / label_shift
  A simple algorithm to identify and correct for label shift.
  ☆21Updated 6 years ago
• sjblim / rmsn_nips_2018
  ☆37Updated 5 years ago
• GT-RIPL / Geometric-Sensitivity-Decomposition
  ☆18Updated 3 years ago
• sungyubkim / DVIB
  A pytorch implementation of DVIB(Deep Variational Information Bottleneck)
  ☆9Updated 5 years ago