75 citations
- Hiroshima UniversityJP11 papers
- The University of TokyoJP3 papers
- Accadis Hochschule Bad HomburgDE1 paper
- Center for Astrophysics Harvard & SmithsonianUS1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Centro de AstrobiologíaES1 paper
- College of CharlestonUS1 paper
- DIPF | Leibniz Institute for Research and Information in EducationDE1 paper
- Ehime UniversityJP1 paper
- ETH ZurichCH1 paper
- Eureka ScientificUS1 paper
- Forschungszentrum JülichDE1 paper
13 papers
Decentralized Multi-Agent System with Trust-Aware Communication
Yepeng Ding, Ahmed Twabi, Junwei Yu +3
The emergence of Large Language Models (LLMs) is rapidly accelerating the development of autonomous multi-agent systems (MAS), paving the way for the Internet of Agents. However, t…
Quantum Optimization Benchmarking Library - The Intractable Decathlon
Thorsten Koch, David E. Bernal Neira, Ying Chen +24
Through recent progress in hardware development, quantum computers have advanced to the point where benchmarking of (heuristic) quantum algorithms at scale is within reach. Particu…
Finite presentations of the mapping class groups of once-stabilized Heegaard splittings
Daiki Iguchi
Let and assume that we are given a genus Heegaard splitting of a closed orientable -manifold with the distance greater than . We prove that the mapping class…
Transfer Learning by Cascaded Network to identify and classify lung nodules for cancer detection
Shah B. Shrey, Lukman Hakim, Muthusubash Kavitha +2
Lung cancer is one of the most deadly diseases in the world. Detecting such tumors at an early stage can be a tedious task. Existing deep learning architecture for lung nodule iden…
Thick isotopy property and the mapping class groups of Heegaard splittings
Daiki Iguchi
We give a necessary and sufficient condition for the fundamental group of the space of Heegaard splittings of an irreducible -manifold to be finitely generated. The condition is…
A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis
Hideaki Hayashi, Taro Shibanoki, Keisuke Shima +2
This paper proposes a probabilistic neural network developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-…