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Isaac Tamblyn

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Learning when to observe: A frugal reinforcement learning framework for a high-cost world

Jul 24, 2023
Colin Bellinger, Mark Crowley, Isaac Tamblyn

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Dynamic Observation Policies in Observation Cost-Sensitive Reinforcement Learning

Jul 05, 2023
Colin Bellinger, Mark Crowley, Isaac Tamblyn

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ChemGymRL: An Interactive Framework for Reinforcement Learning for Digital Chemistry

May 23, 2023
Chris Beeler, Sriram Ganapathi Subramanian, Kyle Sprague, Nouha Chatti, Colin Bellinger, Mitchell Shahen, Nicholas Paquin, Mark Baula, Amanuel Dawit, Zihan Yang, Xinkai Li, Mark Crowley, Isaac Tamblyn

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fintech-kMC: Agent based simulations of financial platforms for design and testing of machine learning systems

Jan 04, 2023
Isaac Tamblyn, Tengkai Yu, Ian Benlolo

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Training neural networks using Metropolis Monte Carlo and an adaptive variant

May 16, 2022
Stephen Whitelam, Viktor Selin, Ian Benlolo, Isaac Tamblyn

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Machine Learning Diffusion Monte Carlo Energy Densities

May 09, 2022
Kevin Ryczko, Jaron T. Krogel, Isaac Tamblyn

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Cellular automata can classify data by inducing trajectory phase coexistence

Apr 06, 2022
Stephen Whitelam, Isaac Tamblyn

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Generative Enriched Sequential Learning (ESL) Approach for Molecular Design via Augmented Domain Knowledge

Apr 05, 2022
Mohammad Sajjad Ghaemi, Karl Grantham, Isaac Tamblyn, Yifeng Li, Hsu Kiang Ooi

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Learning stochastic dynamics and predicting emergent behavior using transformers

Feb 17, 2022
Corneel Casert, Isaac Tamblyn, Stephen Whitelam

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