Isaac Tamblyn - RankMe

44 papers Journal 36Unranked 8

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	Dynamic programming with incomplete information to overcome navigational uncertainty in POMDPs. Canadian AI Chris Beeler, Xinkai Li, Colin Bellinger, Mark Crowley, Maia Fraser, Isaac Tamblyn
2023	J	`jnl`	ChemGymRL: An Interactive Framework for Reinforcement Learning for Digital Chemistry. CoRR 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
2023	—	`conf`	Learning When to Observe: A Frugal Reinforcement Learning Framework for a High-Cost World. PKDD/ECML Workshops (4) Colin Bellinger, Isaac Tamblyn, Mark Crowley
2023	J	`jnl`	Learning when to observe: A frugal reinforcement learning framework for a high-cost world. CoRR Colin Bellinger, Mark Crowley, Isaac Tamblyn
2023	—	`conf`	Time and temporal abstraction in continual learning: tradeoffs, analogies and regret in an active measuring setting. CoLLAs Vincent Létourneau, Colin Bellinger, Isaac Tamblyn, Maia Fraser
2023	J	`jnl`	fintech-kMC: Agent based simulations of financial platforms for design and testing of machine learning systems. CoRR Isaac Tamblyn, Tengkai Yu, Ian Benlolo
2022	—	`conf`	Balancing Information with Observation Costs in Deep Reinforcement Learning. Canadian AI Colin Bellinger, Andriy Drozdyuk, Mark Crowley, Isaac Tamblyn
2022	J	`jnl`	Cellular automata can classify data by inducing trajectory phase coexistence. CoRR Stephen Whitelam, Isaac Tamblyn
2022	—	`conf`	Generative Enriched Sequential Learning (ESL) Approach for Molecular Design via Augmented Domain Knowledge. Canadian AI Mohammad Sajjad Ghaemi, Karl Grantham, Isaac Tamblyn, Yifeng Li, Hsu Kiang Ooi
2022	J	`jnl`	Generative Enriched Sequential Learning (ESL) Approach for Molecular Design via Augmented Domain Knowledge. CoRR Mohammad Sajjad Ghaemi, Karl Grantham, Isaac Tamblyn, Yifeng Li, Hsu Kiang Ooi
2022	J	`jnl`	Learning stochastic dynamics and predicting emergent behavior using transformers. CoRR Corneel Casert, Isaac Tamblyn, Stephen Whitelam
2022	J	`jnl`	Machine Learning Diffusion Monte Carlo Energy Densities. CoRR Kevin Ryczko, Jaron T. Krogel, Isaac Tamblyn
2022	J	`jnl`	Training neural networks using Metropolis Monte Carlo and an adaptive variant. CoRR Stephen Whitelam, Viktor Selin, Ian Benlolo, Isaac Tamblyn
2022	J	`jnl`	Training neural networks using Metropolis Monte Carlo and an adaptive variant. Mach. Learn. Sci. Technol. Stephen Whitelam, Viktor Selin, Ian Benlolo, Corneel Casert, Isaac Tamblyn
2022	J	`jnl`	Twin neural network regression is a semi-supervised regression algorithm. Mach. Learn. Sci. Technol. Sebastian Johann Wetzel, Roger G. Melko, Isaac Tamblyn
2021	—	`conf`	Active Measure Reinforcement Learning for Observation Cost Minimization. Canadian AI Colin Bellinger, Rory Coles, Mark Crowley, Isaac Tamblyn
2021	J	`jnl`	Dynamic programming with partial information to overcome navigational uncertainty in a nautical environment. CoRR Chris Beeler, Xinkai Li, Mark Crowley, Maia Fraser, Isaac Tamblyn
2021	J	`jnl`	Golem: An algorithm for robust experiment and process optimization. CoRR Matteo Aldeghi, Florian Häse, Riley J. Hickman, Isaac Tamblyn, Alán Aspuru-Guzik
2021	J	`jnl`	Interpretable discovery of new semiconductors with machine learning. CoRR Hitarth Choubisa, Petar Todorovic, Joao M. Pina, Darshan H. Parmar, Ziliang Li, Oleksandr Voznyy, Isaac Tamblyn, Edward H. Sargent
2021	J	`jnl`	Scientific Discovery and the Cost of Measurement - Balancing Information and Cost in Reinforcement Learning. CoRR Colin Bellinger, Andriy Drozdyuk, Mark Crowley, Isaac Tamblyn
2021	J	`jnl`	Scientific intuition inspired by machine learning-generated hypotheses. Mach. Learn. Sci. Technol. Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru-Guzik
2021	J	`jnl`	Twin Neural Network Regression is a Semi-Supervised Regression Algorithm. CoRR Sebastian Johann Wetzel, Roger G. Melko, Isaac Tamblyn
2021	J	`jnl`	Watch and learn - a generalized approach for transferrable learning in deep neural networks via physical principles. Mach. Learn. Sci. Technol. Kyle Sprague, Juan Carrasquilla, Stephen Whitelam, Isaac Tamblyn
2021	J	`jnl`	Weakly-supervised multi-class object localization using only object counts as labels. CoRR Kyle Mills, Isaac Tamblyn
2020	J	`jnl`	Active Measure Reinforcement Learning for Observation Cost Minimization. CoRR Colin Bellinger, Rory Coles, Mark Crowley, Isaac Tamblyn
2020	J	`jnl`	Controlled Online Optimization Learning (COOL): Finding the ground state of spin Hamiltonians with reinforcement learning. CoRR Kyle Mills, Pooya Ronagh, Isaac Tamblyn
2020	J	`jnl`	Correspondence between neuroevolution and gradient descent. CoRR Stephen Whitelam, Viktor Selin, Sang-Won Park, Isaac Tamblyn
2020	J	`jnl`	Deep learning and high harmonic generation. CoRR M. Lytova, Michael Spanner, Isaac Tamblyn
2020	J	`jnl`	Dynamical large deviations of two-dimensional kinetically constrained models using a neural-network state ansatz. CoRR Corneel Casert, Tom Vieijra, Stephen Whitelam, Isaac Tamblyn
2020	J	`jnl`	Finding the ground state of spin Hamiltonians with reinforcement learning. Nat. Mach. Intell. Kyle Mills, Pooya Ronagh, Isaac Tamblyn
2020	J	`jnl`	Neuroevolutionary learning of particles and protocols for self-assembly. CoRR Stephen Whitelam, Isaac Tamblyn
2020	—	`conf`	Reinforcement Learning in a Physics-Inspired Semi-Markov Environment. Canadian AI Colin Bellinger, Rory Coles, Mark Crowley, Isaac Tamblyn
2020	J	`jnl`	Reinforcement Learning in a Physics-Inspired Semi-Markov Environment. CoRR Colin Bellinger, Rory Coles, Mark Crowley, Isaac Tamblyn
2020	J	`jnl`	Scientific intuition inspired by machine learning generated hypotheses. CoRR Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru-Guzik
2020	J	`jnl`	Twin Neural Network Regression. CoRR Sebastian Johann Wetzel, Kevin Ryczko, Roger G. Melko, Isaac Tamblyn
2020	J	`jnl`	Watch and learn - a generalized approach for transferrable learning in deep neural networks via physical principles. CoRR Kyle Sprague, Juan Carrasquilla, Stephen Whitelam, Isaac Tamblyn
2019	J	`jnl`	Evolutionary reinforcement learning of dynamical large deviations. CoRR Stephen Whitelam, Daniel Jacobson, Isaac Tamblyn
2019	J	`jnl`	Learning to grow: control of materials self-assembly using evolutionary reinforcement learning. CoRR Stephen Whitelam, Isaac Tamblyn
2019	J	`jnl`	Optimizing thermodynamic trajectories using evolutionary reinforcement learning. CoRR Chris Beeler, Uladzimir Yahorau, Rory Coles, Kyle Mills, Stephen Whitelam, Isaac Tamblyn
2017	J	`jnl`	Deep learning and the Schrödinger equation. CoRR Kyle Mills, Michael Spanner, Isaac Tamblyn
2017	J	`jnl`	Hashkat: large-scale simulations of online social networks. Soc. Netw. Anal. Min. Kevin Ryczko, Adam Domurad, Nicholas Buhagiar, Isaac Tamblyn
2017	J	`jnl`	Sampling algorithms for validation of supervised learning models for Ising-like systems. J. Comput. Phys. Nataliya Portman, Isaac Tamblyn
2016	J	`jnl`	Hashkat: Large-scale simulations of online social networks. CoRR Kevin Ryczko, Adam Domurad, Nicholas Buhagiar, Isaac Tamblyn
2008	—	`conf`	Exploring the High Pressure Phase Diagrams of Light Elements Using Large Scale Ab-initio Molecular Dynamics Simulations. HPCS Isaac Tamblyn, Stanimir A. Bonev