Search Results for author: Taylor W. Killian

Found 7 papers, 4 papers with code

Continuous Time Evidential Distributions for Irregular Time Series

1 code implementation25 Jul 2023 Taylor W. Killian, Haoran Zhang, Thomas Hartvigsen, Ava P. Amini

Prevalent in many real-world settings such as healthcare, irregular time series are challenging to formulate predictions from.

Irregular Time Series Time Series +1

Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning

no code implementations13 Jan 2023 Taylor W. Killian, Sonali Parbhoo, Marzyeh Ghassemi

We find that DistDeD significantly improves over prior discovery approaches, providing indications of the risk 10 hours earlier on average as well as increasing detection by 20%.

Decision Making reinforcement-learning +1

Medical Dead-ends and Learning to Identify High-risk States and Treatments

1 code implementation NeurIPS 2021 Mehdi Fatemi, Taylor W. Killian, Jayakumar Subramanian, Marzyeh Ghassemi

Machine learning has successfully framed many sequential decision making problems as either supervised prediction, or optimal decision-making policy identification via reinforcement learning.

Decision Making

An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare

1 code implementation23 Nov 2020 Taylor W. Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi

Reinforcement Learning (RL) has recently been applied to sequential estimation and prediction problems identifying and developing hypothetical treatment strategies for septic patients, with a particular focus on offline learning with observational data.

Open-Ended Question Answering reinforcement-learning +2

Counterfactually Guided Off-policy Transfer in Clinical Settings

no code implementations20 Jun 2020 Taylor W. Killian, Marzyeh Ghassemi, Shalmali Joshi

Domain shift, encountered when using a trained model for a new patient population, creates significant challenges for sequential decision making in healthcare since the target domain may be both data-scarce and confounded.

counterfactual Decision Making

Learning Robust Representations for Automatic Target Recognition

no code implementations26 Nov 2018 Justin A. Goodwin, Olivia M. Brown, Taylor W. Killian, Sung-Hyun Son

Radio frequency (RF) sensors are used alongside other sensing modalities to provide rich representations of the world.

General Classification Robust classification

Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes

1 code implementation NeurIPS 2017 Taylor W. Killian, Samuel Daulton, George Konidaris, Finale Doshi-Velez

We introduce a new formulation of the Hidden Parameter Markov Decision Process (HiP-MDP), a framework for modeling families of related tasks using low-dimensional latent embeddings.

Transfer Learning

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