68 citations · 120 across the 4 of their papers we have counts for
4 papers
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly
Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger +5
Bayesian Optimisation (BO) refers to a suite of techniques for global optimisation of expensive black box functions, which use introspective Bayesian models of the function to effi…
A Density Functional Tight Binding Layer for Deep Learning of Chemical Hamiltonians
Haichen Li, Christopher Collins, Matteus Tanha +2
Current neural networks for predictions of molecular properties use quantum chemistry only as a source of training data. This paper explores models that use quantum chemistry as an…
Tuning the Molecular Weight Distribution from Atom Transfer Radical Polymerization Using Deep Reinforcement Learning
Haichen Li, Christopher R. Collins, Thomas G. Ribelli +4
We devise a novel technique to control the shape of polymer molecular weight distributions (MWDs) in atom transfer radical polymerization (ATRP). This technique makes use of recent…
Constant Size Molecular Descriptors For Use With Machine Learning
Christopher R. Collins, Geoffrey J. Gordon, O. Anatole von Lilienfeld +1
A set of molecular descriptors whose length is independent of molecular size is developed for machine learning models that target thermodynamic and electronic properties of molecul…