Search Results for author: Christoph Kreisbeck

Found 3 papers, 2 papers with code

PHOENICS: A universal deep Bayesian optimizer

1 code implementation4 Jan 2018 Florian Häse, Loïc M. Roch, Christoph Kreisbeck, Alán Aspuru-Guzik

In this work we introduce PHOENICS, a probabilistic global optimization algorithm combining ideas from Bayesian optimization with concepts from Bayesian kernel density estimation.

Density Estimation Gaussian Processes

Automatic differentiation in quantum chemistry with an application to fully variational Hartree-Fock

1 code implementation22 Nov 2017 Teresa Tamayo-Mendoza, Christoph Kreisbeck, Roland Lindh, Alán Aspuru-Guzik

Automatic Differentiation (AD) is a powerful tool that allows calculating derivatives of implemented algorithms with respect to all of their parameters up to machine precision, without the need to explicitly add any additional functions.

Chemical Physics

Machine Learning for Quantum Dynamics: Deep Learning of Excitation Energy Transfer Properties

no code implementations20 Jul 2017 Florian Häse, Christoph Kreisbeck, Alán Aspuru-Guzik

Understanding the relationship between the structure of light-harvesting systems and their excitation energy transfer properties is of fundamental importance in many applications including the development of next generation photovoltaics.

BIG-bench Machine Learning

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