Name: Patrick Schwab
Type: User
Company: GSK
Bio: Director for Machine Learning and Artificial Intelligence at GSK. Previously: ML at Roche, PhD in ML for Healthcare, ETH Zurich
Twitter: schwabpa
Location: Zurich, Switzerland
Blog: schwabpatrick.com
Patrick Schwab's Projects
π€π€ Attentive Mixtures of Experts (AMEs) are neural network models that learn to output both accurate predictions and estimates of feature importance for individual samples.
A piano scene for the computer graphics class project, using OpenGL, OpenAL, assimp and GLFW.
The COVID-19 Early Warning System (CovEWS) is a real-time early warning system for assessing individual COVID-19 related mortality risk.
The exercises for OOP in CPP class.
Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
My personal website built with Angular and Jekyll.
ππ Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatments from observational data using neural networks.
ππ‘ Distantly Supervised Multitask Networks (DSMT-Nets) are a deep-learning approach to semi-supervised learning that utilises distant supervision through many auxiliary tasks.
πΆπ± A deep-learning approach to automatically extract digital biomarkers for Parkinson's disease from smartphone accelerometers.
A snake clone for GADEL class using the Angle engine.
β€οΈπ± Heart rhythm classification from mobile event recorder data using attentive neural networks.
ββ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.
SKS class excercise. A n-tier application with multiple clients and web services, built on Java EE.
A simple singleton pattern demonstration
A simple Chain Of Responsibility pattern demonstration.
A simple plugin pattern demonstration.
A simple composite pattern demonstration
A simple observer pattern demonstration.
A simple adapter pattern demonstration.