Alternatives and similar repositories for sdcd

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

• Genentech / nodags-flows
  ☆11Updated 3 months ago
• causalbench / causalbench
  ☆55Updated 6 months ago
• uhlerlab / causaldag
  Python package for the creation, manipulation, and learning of Causal DAGs
  ☆155Updated 2 years ago
• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆77Updated 3 years ago
• lazaratan / dyn-gfn
  DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks
  ☆58Updated 2 months ago
• uhlerlab / discrepancy_vae
  code for paper: Identifiability Guarantees for Causal Disentanglement from Soft Interventions
  ☆15Updated 2 years ago
• kevinsbello / dagma
  A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…
  ☆135Updated last year
• rflperry / sparse_shift
  ☆11Updated 3 years ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆39Updated 5 years ago
• Genentech / dcdfg
  ☆28Updated 3 years ago
• chl8856 / SEFS
  Codebase for SEFS: Self-Supervision Enhanced Feature Selection with Correlated Gates
  ☆24Updated 2 years ago
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆34Updated 4 years ago
• alexisbellot / Graphical-modelling-continuous-time
  Graphical modelling with time series data using an ODE model
  ☆12Updated 3 years ago
• bunnech / jkonet
  Proximal Optimal Transport Modeling of Population Dynamics (AISTATS 2022)
  ☆22Updated 2 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆26Updated 3 years ago
• KrishnaswamyLab / MIOFlow
  ☆34Updated last month
• BorgwardtLab / JointMDS
  Official implementation of Joint Multidimensional Scaling
  ☆23Updated 2 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• vios-s / DiffAN
  Diffusion Models for Causal Discovery
  ☆90Updated 2 years ago
• snap-stanford / conformalized-gnn
  Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)
  ☆84Updated 2 years ago
• ratschlab / SVGP-VAE
  Tensorflow implementation for the SVGP-VAE model.
  ☆22Updated 4 years ago
• ermongroup / BCD-Nets
  Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021
  ☆26Updated 4 years ago
• amspector100 / knockpy
  Knockoffs for controlled variable selection
  ☆40Updated 4 months ago
• uhlerlab / actlearn_optint
  Active learning for optimal intervention design in causal models
  ☆16Updated 2 years ago
• gemoran / sparse-vae-code
  ☆31Updated 3 years ago
• tvayer / FGW
  Code for Optimal Transport for structured data with application on graphs
  ☆103Updated 2 years ago
• HongtengXu / s-gwl
  Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching
  ☆44Updated 6 years ago
• thibsej / unbalanced_gromov_wasserstein
  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport
  ☆45Updated 2 years ago
• KevinMoonLab / GRAE
  Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning
  ☆22Updated last year
• KrishnaswamyLab / DiffusionEMD
  Code corresponding to the paper Diffusion Earth Mover's Distance and Distribution Embeddings
  ☆38Updated last year