88 citations · 95 across the 3 of their papers we have counts for
4 papers
Times Square sampling: an adaptive algorithm for free energy estimation
Cristian Predescu, Michael Snarski, Avi Robinson-Mosher +3
Estimating free energy differences, an important problem in computational drug discovery and in a wide range of other application areas, commonly involves a computationally intensi…
Efficient hyperparameter optimization by way of PAC-Bayes bound minimization
John J. Cherian, Andrew G. Taube, Robert T. McGibbon +6
Identifying optimal values for a high-dimensional set of hyperparameters is a problem that has received growing attention given its importance to large-scale machine learning appli…
A deep-learning view of chemical space designed to facilitate drug discovery
Paul Maragakis, Hunter Nisonoff, Brian Cole +1
Drug discovery projects entail cycles of design, synthesis, and testing that yield a series of chemically related small molecules whose properties, such as binding affinity to a gi…
The -series: A separable decomposition for electrostatics computation with improved accuracy
Cristian Predescu, Adam K. Lerer, Ross A. Lippert +4
The evaluation of electrostatic energy for a set of point charges in a periodic lattice is a computationally expensive part of molecular dynamics simulations (and other application…