4 citations · 13 across the 10 of their papers we have counts for
25 papers
-UQ: Accurate Uncertainty Quantification via Anchor Marginalization
Rushil Anirudh, Jayaraman J. Thiagarajan
We present -UQ -- a novel, general-purpose uncertainty estimator using the concept of anchoring in predictive models. Anchoring works by first transforming the input into a tupl…
Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization
Suhas Lohit, Rushil Anirudh, Pavan Turaga
Motion capture (mocap) and time-of-flight based sensing of human actions are becoming increasingly popular modalities to perform robust activity analysis. Applications range from a…
Attribute-Guided Adversarial Training for Robustness to Natural Perturbations
Tejas Gokhale, Rushil Anirudh, Bhavya Kailkhura +3
While existing work in robust deep learning has focused on small pixel-level norm-based perturbations, this may not account for perturbations encountered in several real-world sett…
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…
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…
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,…