5 papers
Perturbative Contrastive Physical Learning
Kyungeun Kim, Amanuel Anteneh, Israel Klich +2
Responses to perturbations are key to understanding physical systems. The ability to contrast such responses by comparing how a system reacts under slightly different conditions pr…
Laser interferometry as a robust neuromorphic platform for machine learning
Amanuel Anteneh, Kyungeun Kim, J. M. Schwarz +2
We present a method for implementing an optical neural network using only linear optical resources, namely field displacement and interferometry applied to coherent states of light…
Cell strain-stiffening drives cell breakout from embedded spheroids
Shabeeb Ameen, Kyungeun Kim, Ligesh Theeyancheri +5
Understanding how cells escape from embedded spheroids requires a mechanical framework linking stress generation within cells, across cells, and between cells and the surrounding e…
Priority-Aware Clinical Pathology Hierarchy Training for Multiple Instance Learning
Sungrae Hong, Kyungeun Kim, Juhyeon Kim +4
Multiple Instance Learning (MIL) is increasingly being used as a support tool within clinical settings for pathological diagnosis decisions, achieving high performance and removing…
Design Principles for Realizable Discrete Surface Embeddings in Physical Systems
Kyungeun Kim, Christian D. Santangelo
The isometric embedding of surfaces in three-dimensional space is fundamental to various physical systems, from elastic sheets to programmable materials. While continuous surfaces…