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HEART: A Platform for the Personalized Management of Diabetes and Cardiovascular Disease at Population Scale With Data From Multiple Sensors
HEART is an open source platform for personalized telehealth at population scale based on data from internet-connected health sensors and data extracted from the electronic medical record. Health sensors include scales, blood pressure monitors, activity trackers, continuous glucose monitors, and insulin pumps. HEART has five independent modules: 1) a data processing module that pulls data in from a variety of devices, 2) an algorithm module that identifies reasons why a provider may want to contact a patient and ranks patients for contact, 3) a visual interface module that summarizes population data and provides additional details for patients selected by the provider, 4) an intervention module that facilitates interventions, and 5) a user tracking module that monitors providers use.
WUT? - A Wrapper for Uncertainty in Tensorflow
Various approximate (Bayesian) inference techniques for estimating both epistemic and aleatoric uncertainty in deep neural networks implemented in eras and TensorFlow (to be officially released by end of May).
BHM: Bayesian Hilbert Maps
Online continuous occupancy mapping with epistemic uncertainty (Numpy and PyTorch)
SimpleLidar: a Simple LIDAR Simulator for Dynamic Environments
A simple 2D LIDAR simulator for dynamic environments. We can define static/moving objects and specify/draw the robot's path on a GUI. The simulator outputs 2D pointcloud data coming from a LIDAR. (Python)
ABHM: Automorphing Bayesian Hilbert Maps
Learning nonstationarity in Bayesian Hilbert maps (TensorFlow and Edward)
BBQ: Black-Box Quantiles
Learning arbitrary RKHS kernels (Python)
POT: Parameter Optimal Transport
Online domain adaptation for occupancy mapping using Optimal Transport (Python)
SpaTUn: Spatio-Temporal Uncertainty
Modeling spatiotemporal epistemic uncertainty with various likelihood models (PyTorch)
AgIS: Agile Information Seeker
Robot exploration using scalable uncertainty maps (PyTorch)