On inverse reinforcement learning and dynamic discrete choice for predicting path choices Drew Kristensen, Emma Frejinger. University of Montreal Masters Thesis, November 2021. [Paper]
Deep Learning to Extract Laboratory Mouse Ultrasonic Vocalizations from Scalograms Adam A Smith, Drew Kristensen. IEEE Bioinformatics and Biomedicine (BIBM), November 2017 (McCormick Research Grant - Summer 2017) [Paper] [Poster] [Presentation]
Neural Networks in the extraction of Mouse Ultrasonic Vocalizations Adam A Smith, Drew Kristensen (Fairchild Research Grant - Summer 2016) [Poster]
Predicting User Features from Social Media data Fracois Mercier, Nicolas Sauthier, Zicong Mo, Drew Kristensen, Yifan Bai. Final project for IFT-6758, Data Science, at the University of Montreal (December 2019) [Paper]
Exploring the effects of different reward function on TSCA learning process Drew Kristensen, Final project for Comp-767, Reinforcement Learning, at McGill University (April 2019) [Paper] [Github]
Probabilistic Graphical Models Final Project Drew Kristensen, Antoine Chehire, Abel Nabli. Final Project for IFT-6269, Probabilistic Graphical Models, at the University of Montreal (November 2018) [Paper]
The Intersection of Reinforcement Learning and Traffic Light Scheduling Drew Kristensen. Capstone in Computer Science Independent Project (Spring 2018) [Paper] [Presentation]
Introduction to Probability Theory in Bayesian Networks Drew Kristensen. Probability Theory Term Paper (Fall 2017) [Paper] [Presentation]
Detection and Enumeration of Stellar SeaLions from aerial photographs in the Bering Sea Drew Kristensen, Patrick Ryan. Intro to Artificial Intelligence Term Project (Spring 2017) [Github] [Paper]
Crazy Chess Drew Kristensen, Noah Johns, Collin Fish, Software Engineering Term Project (Fall 2016) [Github][Demo]