Alternatives and similar repositories for Instance-Based_CFE_TSC

Users that are interested in Instance-Based_CFE_TSC are comparing it to the libraries listed below

• peaclab / CoMTE
  Counterfactual Explanations for Multivariate Time Series Data
  ☆33Updated last year
• josephenguehard / time_interpret
  Unified Model Interpretability Library for Time Series
  ☆60Updated 2 months ago
• JHoelli / Awesome-Time-Series-Explainability
  A list of (post-hoc) XAI for time series
  ☆152Updated 10 months ago
• hturbe / InterpretTime
  Implementation of the InterpretTime framework
  ☆46Updated 2 years ago
• vanderschaarlab / mlforhealthlabpub
  Machine Learning and Artificial Intelligence for Medicine.
  ☆452Updated 2 years ago
• JonathanCrabbe / Dynamask
  This repository contains the implementation of Dynamask, a method to identify the features that are salient for a model to issue its pred…
  ☆76Updated 3 years ago
• Nic5472K / ScientificData2021_HealthGym
  ☆22Updated 2 years ago
• iancovert / Neural-GC
  Granger causality discovery for neural networks.
  ☆222Updated 4 years ago
• ayaabdelsalam91 / TS-Interpretability-Benchmark
  ☆91Updated 3 years ago
• vanderschaarlab / hyperimpute
  A framework for prototyping and benchmarking imputation methods
  ☆186Updated 2 years ago
• ckassaad / causal_discovery_for_time_series
  Causal discovery for time series
  ☆99Updated 3 years ago
• Biwei-Huang / Causal-Discovery-from-Nonstationary-Heterogeneous-Data
  Causal Discovery from Nonstationary/Heterogeneous Data.
  ☆53Updated 4 years ago
• hfawaz / cd-diagram
  Critical difference diagram with Wilcoxon-Holm post-hoc analysis.
  ☆284Updated 2 years ago
• sindhura97 / STraTS
  ☆79Updated 11 months ago
• LuChang-CS / MTGAN
  Code for the paper: Multi-Label Clinical Time-Series Generation via Conditional GAN (IEEE TKDE)
  ☆38Updated 3 years ago
• sanatonek / time_series_explainability
  ☆61Updated 4 years ago
• iancovert / sage
  For calculating global feature importance using Shapley values.
  ☆272Updated last week
• causalens / cdml-neurips2020
  This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…
  ☆62Updated 11 months ago
• wt-hu / pyCausalFS
  pyCausalFS：A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification
  ☆70Updated 4 years ago
• jarrycyx / UNN
  Causal Neural Nerwork
  ☆117Updated 3 weeks ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆54Updated last year
• vanderschaarlab / clairvoyance
  Clairvoyance: a Unified, End-to-End AutoML Pipeline for Medical Time Series
  ☆132Updated 2 years ago
• ChangWeiTan / TS-Extrinsic-Regression
  This repository contains the source code for time series regression.
  ☆102Updated last year
• M-Nauta / TCDF
  Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series
  ☆508Updated 3 years ago
• zzzace2000 / nodegam
  Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"
  ☆47Updated 2 years ago
• vanderschaarlab / DECAF
  DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks
  ☆21Updated last month
• PeterChe1990 / GRU-D
  GRU-D, a GRU-based model with trainable decays for multivariate time series classification with missing values/irregular samplings
  ☆133Updated 2 years ago
• Jeanselme / DynamicDeepHit
  Dynamic Deep Hit - Pytorch implementation
  ☆27Updated last month
• ioanabica / Time-Series-Deconfounder
  Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …
  ☆52Updated 4 years ago
• reml-lab / mTAN
  Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.
  ☆135Updated 4 years ago