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hpi-studyu / fitbitter
Forked from gcappon/fitbitterA Flutter package to make your life easier when dealing with Fitbit APIs.
🗺️ Spatial Join & Enrich any urban layer given any external urban dataset of interest, streamline your urban analysis with Scikit-Learn-Like pipelines, and share your insights with the urban resear…
☂️ Auto-Scikit-Longitudinal (Auto-Sklong) is an automated machine learning (AutoML) library designed to analyse longitudinal data (Classification tasks focussed as of today) using various search me…
☂️ Scikit-longitudinal (Sklong) is an open-source Python library & Scikit-Learn API compliant, tailored to longitudinal machine learning classification tasks. It is ideal for researchers, data scie…
ROS 4 Healthcare: Physiological Human Sensing for Social, Assistive, Rehabilitation, and Medical Robotics
Methods for Specifying, Simulating from and Fitting Causal Models
An OpenSource python package for the analysis of time series data on networks using higher-order and multi-order graphical models.
pathpy is an OpenSource python package for the modeling and analysis of pathways and temporal networks using higher-order and multi-order graphical models
connector: A package for interacting with clinical data sets in the simple way
An Interface to Specify Causal Graphs and Compute Balke Bounds
Code for all experiments in the manuscript "Effect-Invariant Mechanisms for Policy Generalization"
Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at
ODEDiscoveryforLongitudinalHeterogeneousTreatmentEffectsInference
Python Library for Causal and Probabilistic Modeling using Bayesian Networks
Official implementation for NeurIPS23 paper: Causal Discovery from Subsampled Time Series with Proxy Variable
The Paco behavioral science mobile research platform
AmsterdamUMCdb - Freely Accessible ICU database. Please access our Open Access manuscript at https://doi.org/10.1097/CCM.0000000000004916
Python package for machine learning for healthcare using a OMOP common data model
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…
Scalable open-source software to run, develop, and benchmark causal discovery algorithms
Shapley Interactions and Shapley Values for Machine Learning
A Python library that helps data scientists to infer causation rather than observing correlation.
Amortized Inference for Causal Structure Learning, NeurIPS 2022
A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characteri 31BE zation"