activity
20172021
most citedA Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms

4 citations · 9 across the 10 of their papers we have counts for

collaborators

18 papers

physics.flu-dyn2021

Towards replacing physical testing of granular materials with a Topology-based Model

Aniketh Venkat, Attila Gyulassy, Graham Kosiba +5

In the study of packed granular materials, the performance of a sample (e.g., the detonation of a high-energy explosive) often correlates to measurements of a fluid flowing through…

stat.ML2020

Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations

Gemma J. Anderson, Jim A. Gaffney, Brian K. Spears +3

Large-scale numerical simulations are used across many scientific disciplines to facilitate experimental development and provide insights into underlying physical processes, but th…

cs.LG2020

Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models

Jayaraman J. Thiagarajan, Peer-Timo Bremer, Rushil Anirudh +3

A crucial aspect of managing a public health crisis is to effectively balance prevention and mitigation strategies, while taking their socio-economic impact into account. In partic…

cs.LG2020

Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates

Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer +3

Calibrating complex epidemiological models to observed data is a crucial step to provide both insights into the current disease dynamics, i.e.\ by estimating a reproductive number,…

stat.ML2020

Accurate and Robust Feature Importance Estimation under Distribution Shifts

Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Rushil Anirudh +2

With increasing reliance on the outcomes of black-box models in critical applications, post-hoc explainability tools that do not require access to the model internals are often use…

cs.DC2020

Scalable Comparative Visualization of Ensembles of Call Graphs

Suraj P. Kesavan, Harsh Bhatia, Abhinav Bhatele +3

Optimizing the performance of large-scale parallel codes is critical for efficient utilization of computing resources. Code developers often explore various execution parameters, s…