20 citations · 56 across the 24 of their papers we have counts for
21 papers
Quantum Gradient Class Activation Map for Model Interpretability
Hsin-Yi Lin, Huan-Hsin Tseng, Samuel Yen-Chi Chen +1
Quantum machine learning (QML) has recently made significant advancements in various topics. Despite the successes, the safety and interpretability of QML applications have not bee…
Quantum Machine Learning Architecture Search via Deep Reinforcement Learning
Xin Dai, Tzu-Chieh Wei, Shinjae Yoo +1
The rapid advancement of quantum computing (QC) and machine learning (ML) has given rise to the burgeoning field of quantum machine learning (QML), aiming to capitalize on the stre…
Automated and Holistic Co-design of Neural Networks and ASICs for Enabling In-Pixel Intelligence
Shubha R. Kharel, Prashansa Mukim, Piotr Maj +4
Extreme edge-AI systems, such as those in readout ASICs for radiation detection, must operate under stringent hardware constraints such as micron-level dimensions, sub-milliwatt po…
Studying the Impact of Latent Representations in Implicit Neural Networks for Scientific Continuous Field Reconstruction
Wei Xu, Derek Freeman DeSantis, Xihaier Luo +5
Learning a continuous and reliable representation of physical fields from sparse sampling is challenging and it affects diverse scientific disciplines. In a recent work, we present…
Extracting Protein-Protein Interactions (PPIs) from Biomedical Literature using Attention-based Relational Context Information
Gilchan Park, Sean McCorkle, Carlos Soto +2
Because protein-protein interactions (PPIs) are crucial to understand living systems, harvesting these data is essential to probe disease development and discern gene/protein funct…
An Evaluation of Real-time Adaptive Sampling Change Point Detection Algorithm using KCUSUM
Vijayalakshmi Saravanan, Perry Siehien, Shinjae Yoo +4
Detecting abrupt changes in real-time data streams from scientific simulations presents a challenging task, demanding the deployment of accurate and efficient algorithms. Identifyi…