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5 papers · 1 filter
Concept-based model explanations for Electronic Health Records
Diana Mincu, Eric Loreaux, Shaobo Hou +7
Recurrent Neural Networks (RNNs) are often used for sequential modeling of adverse outcomes in electronic health records (EHRs) due to their ability to encode past clinical states.…
Deep Reinforcement Learning for Tactile Robotics: Learning to Type on a Braille Keyboard
Alex Church, John Lloyd, Raia Hadsell +1
Artificial touch would seem well-suited for Reinforcement Learning (RL), since both paradigms rely on interaction with an environment. Here we propose a new environment and set of…
Grale: Designing Networks for Graph Learning
Jonathan Halcrow, Alexandru Moşoi, Sam Ruth +1
How can we find the right graph for semi-supervised learning? In real world applications, the choice of which edges to use for computation is the first step in any graph learning p…
Predicting the long-term stability of compact multiplanet systems
Daniel Tamayo, Miles Cranmer, Samuel Hadden +11
We combine analytical understanding of resonant dynamics in two-planet systems with machine learning techniques to train a model capable of robustly classifying stability in compac…
Self-Supervised Reinforcement Learning for Recommender Systems
Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis +1
In session-based or sequential recommendation, it is important to consider a number of factors like long-term user engagement, multiple types of user-item interactions such as clic…