Paper-Conference

ROSE: RADICAL Orchestrator for Surrogate Exploration

Scientific computing faces challenges in building scalable surrogate models due to expensive simulations, complex data workflows, and tight coupling with active learning—issues …

Aymen Alsaadi
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Meta-learning based Active Learning Approach for Computer-Assisted Pace-Mapping

Ventricular tachycardia (VT) is a major cause of cardiac death, and precise localization of its source via pace-mapping is critical but invasive and time-consuming. We propose a …

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Pradeep Bajracharya
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AI-Assisted Pace-Mapping using Continual-Learning Methods in Bayesian Optimization

Ventricular tachycardia (VT) is a leading cause of sudden cardiac death, and pace-mapping-guided catheter ablation is key to treatment but remains labor-intensive and inefficient. …

Dylan O'Hara
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Active learning based Cardiac Tissue Parameter Estimation for Personalized model exploiting predictive uncertainty featured image

Active learning based Cardiac Tissue Parameter Estimation for Personalized model exploiting predictive uncertainty

Personalized cardiac models are crucial intervention tools for a multitude of cardiac health issues. As cardiac simulations become more complex and expensive, machine learning (ML) …

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Pradeep Bajracharya
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Semi-supervised Medical Image Classification with Global Latent Mixing featured image

Semi-supervised Medical Image Classification with Global Latent Mixing

In this work, we argue that regularizing the global smoothness of neural functions by filling the void in between data points can further improve SSL. We present a novel SSL …

Prashnna K. Gyawali
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Indoor Odometry and Point Cloud Mapping featured image

Indoor Odometry and Point Cloud Mapping

Indoor localization and mapping is an important problem with many applications such as emergency response, architectural modeling, and historical preservation. In this project, a …

Prabhat Sanu Ligal
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