18 citations · 49 across the 11 of their papers we have counts for
22 papers
Neural Architecture Search Algorithms for Quantum Autoencoders
Ankit Kulshrestha, Xiaoyuan Liu, Hayato Ushijima-Mwesigwa +1
The design of quantum circuits is currently driven by the specific objectives of the quantum algorithm in question. This approach thus relies on a significant manual effort by the…
PrecipDiff: Leveraging image diffusion models to enhance satellite-based precipitation observations
Ting-Yu Dai, Hayato Ushijima-Mwesigwa
A recent report from the World Meteorological Organization (WMO) highlights that water-related disasters have caused the highest human losses among natural disasters over the past…
QAdaPrune: Adaptive Parameter Pruning For Training Variational Quantum Circuits
Ankit Kulshrestha, Xiaoyuan Liu, Hayato Ushijima-Mwesigwa +2
In the present noisy intermediate scale quantum computing era, there is a critical need to devise methods for the efficient implementation of gate-based variational quantum circuit…
Learning To Optimize Quantum Neural Network Without Gradients
Ankit Kulshrestha, Xiaoyuan Liu, Hayato Ushijima-Mwesigwa +1
Quantum Machine Learning is an emerging sub-field in machine learning where one of the goals is to perform pattern recognition tasks by encoding data into quantum states. This exte…
Towards Practical Explainability with Cluster Descriptors
Xiaoyuan Liu, Ilya Tyagin, Hayato Ushijima-Mwesigwa +2
With the rapid development of machine learning, improving its explainability has become a crucial research goal. We study the problem of making the clusters more explainable by inv…
Partitioning Dense Graphs with Hardware Accelerators
Xiaoyuan Liu, Hayato Ushijima-Mwesigwa, Indradeep Ghosh +1
Graph partitioning is a fundamental combinatorial optimization problem that attracts a lot of attention from theoreticians and practitioners due to its broad applications. From mul…