94 citations · 139 across the 5 of their papers we have counts for
24 papers
Event Classification with Multi-step Machine Learning
Masahiko Saito, Tomoe Kishimoto, Yuya Kaneta +6
The usefulness and value of Multi-step Machine Learning (ML), where a task is organized into connected sub-tasks with known intermediate inference goals, as opposed to a single lar…
Quantum Gate Pattern Recognition and Circuit Optimization for Scientific Applications
Wonho Jang, Koji Terashi, Masahiko Saito +7
There is no unique way to encode a quantum algorithm into a quantum circuit. With limited qubit counts, connectivities, and coherence times, circuit optimization is essential to ma…
An Improvement of Object Detection Performance using Multi-step Machine Learnings
Tomoe Kishimoto, Masahiko Saito, Junichi Tanaka +3
Connecting multiple machine learning models into a pipeline is effective for handling complex problems. By breaking down the problem into steps, each tackled by a specific componen…
Search for displaced leptons in TeV collisions with the ATLAS detector
ATLAS Collaboration
A search for charged leptons with large impact parameters using 139 fb of TeV collision data from the ATLAS detector at the LHC is presented, addressing…
Search for resonances decaying into a weak vector boson and a Higgs boson in the fully hadronic final state produced in protonproton collisions at TeV with the ATLAS detector
ATLAS Collaboration
A search for heavy resonances decaying into a or boson and a Higgs boson produced in protonproton collisions at the Large Hadron Collider at TeV is prese…
Event Classification with Quantum Machine Learning in High-Energy Physics
Koji Terashi, Michiru Kaneda, Tomoe Kishimoto +3
We present studies of quantum algorithms exploiting machine learning to classify events of interest from background events, one of the most representative machine learning applicat…