On the calibration of compartmental epidemiological models

1 code implementation • 9 Dec 2023 • Nikunj Gupta, Anh Mai, Azza Abouzied, Dennis Shasha

Finally, we discuss how the calibration of parameters of epidemiological compartmental models is an emerging field that has the potential to improve the accuracy of disease modeling and public health decision-making.

Decision Making Reinforcement Learning (RL)

Efficient ResNets: Residual Network Design

1 code implementation • 21 Jun 2023 • Aditya Thakur, Harish Chauhan, Nikunj Gupta

We show that our ResNet achieves a test accuracy of 96. 04% on CIFAR-10 which is much higher than ResNet18 (which has greater than 11 million trainable parameters) when equipped with a number of training strategies and suitable ResNet hyperparameters.

Image Classification

Understanding human mobility patterns in Chicago: an analysis of taxi data using clustering techniques

1 code implementation • 21 Jun 2023 • Harish Chauhan, Nikunj Gupta, Zoe Haskell-Craig

This analysis will provide a sense of which neighborhoods individuals are using taxis to travel between, suggesting regions to focus new public transit development efforts.

CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning

1 code implementation • 19 Jun 2023 • Nikunj Gupta, Somjit Nath, Samira Ebrahimi Kahou

Before taking actions in an environment with more than one intelligent agent, an autonomous agent may benefit from reasoning about the other agents and utilizing a notion of a guarantee or confidence about the behavior of the system.

Conformal Prediction Decision Making +2

Predicting blood pressure under circumstances of missing data: An analysis of missing data patterns and imputation methods using NHANES

1 code implementation • 1 May 2023 • Harish Chauhan, Nikunj Gupta, Zoe Haskell-Craig

Motivated by the pervasiveness of missing data in the NHANES dataset, we will conduct an analysis of imputation methods under different simulated patterns of missing data.

Imputation

Planning Multiple Epidemic Interventions with Reinforcement Learning

1 code implementation • 30 Jan 2023 • Anh Mai, Nikunj Gupta, Azza Abouzied, Dennis Shasha

We illustrate how to effectively apply state-of-the-art actor-critic reinforcement learning algorithms (PPO and SAC) to search for plans that minimize overall costs.

reinforcement-learning Reinforcement Learning (RL)

Prediction of drug effectiveness in rheumatoid arthritis patients based on machine learning algorithms

1 code implementation • 14 Oct 2022 • Shengjia Chen, Nikunj Gupta, Woodward B. Galbraith, Valay Shah, Jacopo Cirrone

This study introduced a Drug Response Prediction (DRP) framework with two main goals: 1) design a data processing pipeline to extract information from tabular clinical data, and then preprocess it for functional use, and 2) predict RA patient's responses to drugs and evaluate classification models' performance.

Binary Classification Classification +1

HAMMER: Multi-Level Coordination of Reinforcement Learning Agents via Learned Messaging

1 code implementation • 18 Jan 2021 • Nikunj Gupta, G Srinivasaraghavan, Swarup Kumar Mohalik, Nishant Kumar, Matthew E. Taylor

This paper considers the case where there is a single, powerful, \emph{central agent} that can observe the entire observation space, and there are multiple, low-powered \emph{local agents} that can only receive local observations and are not able to communicate with each other.

Multi-agent Reinforcement Learning reinforcement-learning +2

Deploying a Task-based Runtime System on Raspberry Pi Clusters

1 code implementation • 8 Oct 2020 • Nikunj Gupta, Steve R. Brandt, Bibek Wagle, Nanmiao, Alireza Kheirkhahan, Patrick Diehl, Hartmut Kaiser, Felix W. Baumann

Here we describe our efforts to configure and benchmark the use of a Raspberry Pi cluster with the HPX/Phylanx platform (normally intended for use with HPC applications) and document the lessons we learned.

Distributed, Parallel, and Cluster Computing