Demon in the Machine: Learning to Extract Work and Absorb Entropy from Fluctuating Nanosystems by Stephen Whitelam

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

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Learning protocols for the fast and efficient control of active matter by Corneel Casert, Stephen Whitelam

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Learning stochastic dynamics and predicting emergent behavior using transformers by Corneel Casert, Isaac Tamblyn, Stephen Whitelam

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The Ramachandran Number: An Order Parameter for Protein Geometry. by Ranjan V Mannige, Joyjit Kundu, Stephen Whitelam

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Insights into the Structure and Energy of DNA Nanoassemblies by Andreas Jaekel, Pascal Lill, Stephen Whitelam, Barbara Saccà

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Correspondence between neuroevolution and gradient descent by Stephen Whitelam, Viktor Selin, Sang-Won Park, Isaac Tamblyn

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Common Physical Framework Explains Phase Behavior and Dynamics of Atomic, Molecular, and Polymeric Network Formers by Stephen Whitelam, Isaac Tamblyn, Thomas K. Haxton, Maria B. Wieland, Neil R. Champness, Juan P. Garrahan, Peter H. Beton

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Ordering, flexibility and frustration in arrays of porphyrin nanorings by Alex Summerfield, Matteo Baldoni, Dmitry V. Kondratuk, Harry L. Anderson, Stephen Whitelam, Juan P. Garrahan, Elena Besley, Peter H. Beton

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