Alternatives and similar repositories for knncmi

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

• amber0309 / HSIC
  Python code of Hilbert-Schmidt Independence Criterion
  ☆88Updated 3 years ago
• iancovert / Neural-GC
  Granger causality discovery for neural networks.
  ☆228Updated 4 years ago
• paulbrodersen / entropy_estimators
  Estimators for the entropy and other information theoretic quantities of continuous distributions
  ☆145Updated last year
• loeweX / AmortizedCausalDiscovery
  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
  ☆218Updated 3 years ago
• ckassaad / causal_discovery_for_time_series
  Causal discovery for time series
  ☆100Updated 3 years ago
• BorisMuzellec / MissingDataOT
  A Pytorch implementation of missing data imputation using optimal transport.
  ☆103Updated 4 years ago
• GAMES-UChile / Wasserstein-Fourier
  ☆15Updated 4 years ago
• wt-hu / pyCausalFS
  pyCausalFS：A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification
  ☆70Updated 4 years ago
• ratschlab / GP-VAE
  TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155
  ☆142Updated 2 years ago
• mvlearn / mvlearn
  Python package for multi-view machine learning
  ☆212Updated last year
• hijoe320 / MVGC
  A simple Multivariate Granger Causality (MVGC) python tool rewritten from part of Matlab MVGC toolbox
  ☆23Updated 7 years ago
• i6092467 / GVAR
  An interpretable framework for inferring nonlinear multivariate Granger causality based on self-explaining neural networks.
  ☆77Updated 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…
  ☆125Updated last year
• juangamella / ges
  Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search…
  ☆60Updated 6 months ago
• jameschapman19 / cca_zoo
  Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic methods in a scikit-learn…
  ☆212Updated last year
• mfbalin / Concrete-Autoencoders
  ☆119Updated 3 years ago
• siamakz / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆48Updated 6 years ago
• notsebastiano / transfer_entropy
  Transfer Entropy between two time series - Implementation in Python
  ☆46Updated 6 months ago
• jarrycyx / UNN
  Causal Neural Nerwork
  ☆128Updated 3 months ago
• kurowasan / GraN-DAG
  ☆96Updated 2 years ago
• scikit-adaptation / skada
  Domain adaptation toolbox compatible with scikit-learn and pytorch
  ☆133Updated 2 weeks ago
• sakhanna / SRU_for_GCI
  Statistical Recurrent Unit based time series generative models for detecting nonlinear Granger causality
  ☆36Updated 4 years ago
• sudiptodip15 / CCMI
  Classifier based mutual information, conditional mutual information estimation; conditional independence testing
  ☆34Updated 6 years ago
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆33Updated 4 years ago
• zzzace2000 / nodegam
  Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"
  ☆46Updated 3 years ago
• pamattei / miwae
  Implementation of the MIWAE method for deep generative modelling of incomplete data sets.
  ☆41Updated last year
• lmz123321 / proxy_causal_discovery
  Official implementation for NeurIPS23 paper: Causal Discovery from Subsampled Time Series with Proxy Variable
  ☆31Updated last year
• yangalan123 / TemporalPointProcessPapers
  Paper lists for Temporal Point Process
  ☆113Updated 2 months ago
• IvanoLauriola / MKLpy
  A package for Multiple Kernel Learning in Python
  ☆132Updated 2 years ago
• jsvir / idc
  Interpretable Deep Clustering for Tabular Data (ICML 2024)
  ☆16Updated last month