papers

Publications (5)

stat.ML2024

Topological Interpretability for Deep-Learning

Adam Spannaus, Heidi A. Hanson, Lynne Penberthy +1

With the growing adoption of AI-based systems across everyday life, the need to understand their decision-making mechanisms is correspondingly increasing. The level at which we can…

cs.LG2022

Why I'm not Answering: Understanding Determinants of Classification of an Abstaining Classifier for Cancer Pathology Reports

Sayera Dhaubhadel, Jamaludin Mohd-Yusof, Kumkum Ganguly +13

Safe deployment of deep learning systems in critical real world applications requires models to make very few mistakes, and only under predictable circumstances. In this work, we a…

cs.LG2024

Adiabatic Quantum Support Vector Machines

Prasanna Date, Dong Jun Woun, Kathleen Hamilton +7

Adiabatic quantum computers can solve difficult optimization problems (e.g., the quadratic unconstrained binary optimization problem), and they seem well suited to train machine le…

cs.AI2018

Precision Medicine as an Accelerator for Next Generation Cognitive Supercomputing

Edmon Begoli, Jim Brase, Bambi DeLaRosa +6

In the past several years, we have taken advantage of a number of opportunities to advance the intersection of next generation high-performance computing AI and big data technologi…

cs.CL2021

Integration of Domain Knowledge using Medical Knowledge Graph Deep Learning for Cancer Phenotyping

Mohammed Alawad, Shang Gao, Mayanka Chandra Shekar +9

A key component of deep learning (DL) for natural language processing (NLP) is word embeddings. Word embeddings that effectively capture the meaning and context of the word that th…