activity
20192022
most citedGraph Neural Network Architecture Search for Molecular Property Prediction

5 citations · 13 across the 14 of their papers we have counts for

collaborators

34 papers

cs.DC2022

A Taxonomy of Error Sources in HPC I/O Machine Learning Models

Mihailo Isakov, Mikaela Currier, Eliakin del Rosario +6

I/O efficiency is crucial to productivity in scientific computing, but the increasing complexity of the system and the applications makes it difficult for practitioners to understa…

physics.data-an2022

Classification of events from -induced reactions in the MUSIC detector via statistical and ML methods

Krishnan Raghavan, Melina L. Avila, Prasanna Balaprakash +2

The Multi-Sampling Ionization Chamber (MUSIC) detector is typically used to measure nuclear reaction cross sections relevant for nuclear astrophysics, fusion studies, and other app…

physics.flu-dyn20212 cited

Data-Driven Modeling of Coarse Mesh Turbulence for Reactor Transient Analysis Using Convolutional Recurrent Neural Networks

Yang Liu, Rui Hu, Adam Kraus +2

Advanced nuclear reactors often exhibit complex thermal-fluid phenomena during transients. To accurately capture such phenomena, a coarse-mesh three-dimensional (3-D) modeling capa…

cs.PL2021

Customized Monte Carlo Tree Search for LLVM/Polly's Composable Loop Optimization Transformations

Jaehoon Koo, Prasanna Balaprakash, Michael Kruse +3

Polly is the LLVM project's polyhedral loop nest optimizer. Recently, user-directed loop transformation pragmas were proposed based on LLVM/Clang and Polly. The search space expose…

cs.LG2021

Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization (extended version)

Xingfu Wu, Michael Kruse, Prasanna Balaprakash +4

In this paper, we develop a ytopt autotuning framework that leverages Bayesian optimization to explore the parameter space search and compare four different supervised learning met…

q-bio.QM2021

A cross-study analysis of drug response prediction in cancer cell lines

Fangfang Xia, Jonathan Allen, Prasanna Balaprakash +21

To enable personalized cancer treatment, machine learning models have been developed to predict drug response as a function of tumor and drug features. However, most algorithm deve…