Search Results for author: Andrew J. Ballard

Found 6 papers, 4 papers with code

Normalizing flows for atomic solids

1 code implementation16 Nov 2021 Peter Wirnsberger, George Papamakarios, Borja Ibarz, Sébastien Racanière, Andrew J. Ballard, Alexander Pritzel, Charles Blundell

We present a machine-learning approach, based on normalizing flows, for modelling atomic solids.

Targeted free energy estimation via learned mappings

no code implementations12 Feb 2020 Peter Wirnsberger, Andrew J. Ballard, George Papamakarios, Stuart Abercrombie, Sébastien Racanière, Alexander Pritzel, Danilo Jimenez Rezende, Charles Blundell

Here, we cast Targeted FEP as a machine learning problem in which the mapping is parameterized as a neural network that is optimized so as to increase overlap.

Metacontrol for Adaptive Imagination-Based Optimization

1 code implementation7 May 2017 Jessica B. Hamrick, Andrew J. Ballard, Razvan Pascanu, Oriol Vinyals, Nicolas Heess, Peter W. Battaglia

The metacontroller component is a model-free reinforcement learning agent, which decides both how many iterations of the optimization procedure to run, as well as which model to consult on each iteration.

Decision Making

Perspective: Energy Landscapes for Machine Learning

no code implementations23 Mar 2017 Andrew J. Ballard, Ritankar Das, Stefano Martiniani, Dhagash Mehta, Levent Sagun, Jacob D. Stevenson, David J. Wales

Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences.

BIG-bench Machine Learning

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