Stephen Whitelam

According to our database, Stephen Whitelam authored at least 16 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

How to train your demon to do fast information erasure without heat production.

Stephen Whitelam

CoRR, 2023

2022

Training neural networks using Metropolis Monte Carlo and an adaptive variant.

Stephen Whitelam, Viktor Selin, Ian Benlolo, Corneel Casert, Isaac Tamblyn

Mach. Learn. Sci. Technol., December, 2022

Demon in the machine: learning to extract work and absorb entropy from fluctuating nanosystems.

Stephen Whitelam

CoRR, 2022

Training neural networks using Metropolis Monte Carlo and an adaptive variant.

Stephen Whitelam, Viktor Selin, Ian Benlolo, Isaac Tamblyn

CoRR, 2022

Cellular automata can classify data by inducing trajectory phase coexistence.

Stephen Whitelam, Isaac Tamblyn

CoRR, 2022

Learning stochastic dynamics and predicting emergent behavior using transformers.

Corneel Casert, Isaac Tamblyn, Stephen Whitelam

CoRR, 2022

2021

Watch and learn - a generalized approach for transferrable learning in deep neural networks via physical principles.

Kyle Sprague, Juan Carrasquilla, Stephen Whitelam, Isaac Tamblyn

Mach. Learn. Sci. Technol., 2021

Improving the Accuracy of Nearest-Neighbor Classification Using Principled Construction and Stochastic Sampling of Training-Set Centroids.

Stephen Whitelam

Entropy, 2021

2020

Neuroevolutionary learning of particles and protocols for self-assembly.

Stephen Whitelam, Isaac Tamblyn

CoRR, 2020

Dynamical large deviations of two-dimensional kinetically constrained models using a neural-network state ansatz.

Corneel Casert, Tom Vieijra, Stephen Whitelam, Isaac Tamblyn

CoRR, 2020

Correspondence between neuroevolution and gradient descent.

Stephen Whitelam, Viktor Selin, Sang-Won Park, Isaac Tamblyn

CoRR, 2020

2019

Learning to grow: control of materials self-assembly using evolutionary reinforcement learning.

Stephen Whitelam, Isaac Tamblyn

CoRR, 2019

Evolutionary reinforcement learning of dynamical large deviations.

Stephen Whitelam, Daniel Jacobson, Isaac Tamblyn

CoRR, 2019

Optimizing thermodynamic trajectories using evolutionary reinforcement learning.

Chris Beeler, Uladzimir Yahorau, Rory Coles, Kyle Mills, Stephen Whitelam, Isaac Tamblyn

CoRR, 2019

2018

Simple coarse graining and sampling strategies for image recognition.

Stephen Whitelam

CoRR, 2018

2014

Development and use of an atomistic CHARMM-based forcefield for peptoid simulation.

Dina T. Mirijanian, Ranjan V. Mannige, Ronald N. Zuckermann, Stephen Whitelam

J. Comput. Chem., 2014