activity
20152021
most citedScalable Bayesian Optimization Using Deep Neural Networks

438 citations · 508 across the 12 of their papers we have counts for

collaborators
Showing 2017Show all

8 papers · 1 filter

cs.DC201710 cited

Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer

Amrita Mathuriya, Thorsten Kurth, Vivek Rane +5

We explore scaling of the standard distributed Tensorflow with GRPC primitives on up to 512 Intel Xeon Phi (KNL) nodes of Cori supercomputer with synchronous stochastic gradient de…

cs.AI20177 cited

Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators

Mario Lezcano Casado, Atilim Gunes Baydin, David Martinez Rubio +8

We consider the problem of Bayesian inference in the family of probabilistic models implicitly defined by stochastic generative models of data. In scientific fields ranging from po…

hep-ex20171 cited

Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC

Wahid Bhimji, Steven Andrew Farrell, Thorsten Kurth +3

There has been considerable recent activity applying deep convolutional neural nets (CNNs) to data from particle physics experiments. Current approaches on ATLAS/CMS have largely f…

astro-ph.CO20176 cited

Galactos: Computing the Anisotropic 3-Point Correlation Function for 2 Billion Galaxies

Brian Friesen, Md. Mostofa Ali Patwary, Brian Austin +8

The nature of dark energy and the complete theory of gravity are two central questions currently facing cosmology. A vital tool for addressing them is the 3-point correlation funct…

cs.DC20175 cited

An Assessment of Data Transfer Performance for Large-Scale Climate Data Analysis and Recommendations for the Data Infrastructure for CMIP6

Eli Dart, Michael F. Wehner, Prabhat

We document the data transfer workflow, data transfer performance, and other aspects of staging approximately 56 terabytes of climate model output data from the distributed Coupled…

cs.PF201719 cited

Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data

Thorsten Kurth, Jian Zhang, Nadathur Satish +12

This paper presents the first, 15-PetaFLOP Deep Learning system for solving scientific pattern classification problems on contemporary HPC architectures. We develop supervised conv…