Deep Learning

Quantum Gravity Meets Quantum Computing
Matrix quantum mechanics plays various important roles in theoretical physics, such as a holographic description of quantum black …
Nov 8, 2021 9:07 AM — Nov 12, 2021 9:07 AM QTML 2021 - Virtual conference (Zoom) - Hosted by RIKEN and RIKEN AIP
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Quantum Gravity Meets Quantum Computing
Quantum gravity in the lab. Matrix quantum mechanics meets quantum computing
Matrix quantum mechanics plays various important roles in theoretical physics, such as a holographic description of quantum black …
Oct 26, 2021 4:00 PM — 5:00 PM NSCL/FRIB Theory Seminar, Michigan State University, East Lansing, MI, USA
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Quantum gravity in the lab. Quantum computing and deep learning solutions
Quantum mechanics is at the core of our understanding of the subatomic world. Moreover, it is driving a new industry based on quantum …
Oct 21, 2021 4:00 PM — 5:00 PM AI Paper Reading, Special Session, Infineon Technologies, Munich, Germany
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Benchmarking quantum algorithms for quantum field theory
Can we use quantum computing to answer important questions in quantum field theory? Once we can formulate the problem on a quantum …
Oct 20, 2021 4:00 PM — 5:00 PM Joint workshop on Quantum Computing, R-CCS, IHPC, CQT, NSCC, Singapore
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Simulation-based inference for multi-type cortical circuits.
In many scientific fields, simulators for dynamical systems generate a massive amount of data. One of the crucial tasks scientists are …
Oct 7, 2021 — RIKEN-OIST Joint Symposium on AI/Data and Neuroscience
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Simulation-based inference for multi-type cortical circuits.
A deep learning and hybrid quantum-classical approach to matrix quantum mechanics
Matrix quantum mechanics plays various important roles in theoretical physics, such as a holographic description of quantum black …
Sep 22, 2021 4:00 PM — 5:00 PM Computational Quantum Science Laboratory, EPFL, Lausanne
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Matrix Model simulations using Quantum Computing, Deep Learning, and Lattice Monte Carlo
We study the two matrix models using deep learning methods and quantum simulations. We benchmark the results against lattice Monte Carlo simulations.
Enrico Rinaldi, Xizhi Han, Mohammad Hassan, Yuan Feng, Franco Nori, Michael McGuigan, Masanori Hanada
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Matrix Model simulations using Quantum Computing, Deep Learning, and Lattice Monte Carlo
Introduction to simulation-based inference
In many scientific fields, ranging from astrophysics to particle physics and neuroscience, simulators for dynamical systems generate a …
Jul 6, 2021 4:00 PM — 5:00 PM Center for Brain Science (CBS), RIKEN, Wako
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Introduction to simulation-based inference
Viewpoint: Machine Learning Tackles Spacetime
Neural networks enable an important calculation in a popular approach to unifying quantum mechanics with general relativity
Enrico Rinaldi
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Viewpoint: Machine Learning Tackles Spacetime
The Data Science of Physics
Applications of Machine Learning to Particle Physics
Jun 13, 2019 4:00 PM — 5:00 PM Arithmer Inc., Tokyo
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The Data Science of Physics