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6 papers · 1 filter
Augmenting Flight Training with AI to Efficiently Train Pilots
Michael Guevarra, Srijita Das, Christabel Wayllace +3
We propose an AI-based pilot trainer to help students learn how to fly aircraft. First, an AI agent uses behavioral cloning to learn flying maneuvers from qualified flight instruct…
Prototyping three key properties of specific curiosity in computational reinforcement learning
Nadia M. Ady, Roshan Shariff, Johannes Günther +1
Curiosity for machine agents has been a focus of intense research. The study of human and animal curiosity, particularly specific curiosity, has unearthed several properties that w…
Fair Sequential Selection Using Supervised Learning Models
Mohammad Mahdi Khalili, Xueru Zhang, Mahed Abroshan
We consider a selection problem where sequentially arrived applicants apply for a limited number of positions/jobs. At each time step, a decision maker accepts or rejects the given…
Transforming Gaussian Processes With Normalizing Flows
Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch +1
Gaussian Processes (GPs) can be used as flexible, non-parametric function priors. Inspired by the growing body of work on Normalizing Flows, we enlarge this class of priors through…
Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations
Ioana Bica, Ahmed M. Alaa, James Jordon +1
Identifying when to give treatments to patients and how to select among multiple treatments over time are important medical problems with a few existing solutions. In this paper, w…
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis
Ahmed M. Alaa, Scott Hu, Mihaela van der Schaar
Critically ill patients in regular wards are vulnerable to unanticipated adverse events which require prompt transfer to the intensive care unit (ICU). To allow for accurate progno…