CERN Accelerating science

CERN-wide meetings, trainings and events

新增:
2023-12-01
08:57
HPC Collaborative Source and Standards at NVIDIA / Adelstein Lelbach, Bryce (speaker) (NVIDIA)
2023 - 0:43:40. Open Science events; CERN Open Source Program Office (OSPO) Inaugural Event External links: Talk details; Event details In : CERN Open Source Program Office (OSPO) Inaugural Event

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2023-11-30
15:44
OSPO of the World Health Organization / Mbuthia, Samuel (speaker) (WHO)
2023 - 0:31:21. Open Science events; CERN Open Source Program Office (OSPO) Inaugural Event External links: Talk details; Event details In : CERN Open Source Program Office (OSPO) Inaugural Event

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2023-11-29
16:26
WLCG Monitoring / Mc Kee, Shawn (speaker) (University of Michigan (US)) ; Andreeva, Julia (speaker) (CERN) ; Weitzel, Derek (speaker) (University of Nebraska Lincoln (US)) ; Forti, Alessandra (speaker) (University of Manchester (GB)) ; Garrido Bear, Borja (speaker) (CERN)
2023 - 0:30:01. DOMA; Data Challenge 2024 Workshop External links: Talk details; Event details In : Data Challenge 2024 Workshop

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2023-11-29
15:32
Quick Acronym Introduction: "OSPO=Open Source Program Office" / Tenaglia, Giacomo (speaker) (CERN)
2023 - 0:08:47. Open Science events; CERN Open Source Program Office (OSPO) Inaugural Event External links: Talk details; Event details In : CERN Open Source Program Office (OSPO) Inaugural Event

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2023-11-29
10:27
XRootD (REMOTE) / Yang, Wei (speaker) (SLAC National Accelerator Laboratory (US)) ; Hanushevsky, Andrew (speaker) (Unknown) ; Hanushevsky, Andrew (speaker) (STANFORD LINEAR ACCELERATOR CENTER) ; Hanushevsky, Andrew (speaker) (Stanford University/SLAC) ; Hanushevsky, Andrew Bohdan (speaker) (SLAC National Accelerator Laboratory (US))
2023 - 0:16:04. DOMA; Data Challenge 2024 Workshop External links: Talk details; Event details In : Data Challenge 2024 Workshop

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2023-11-29
10:27
KEYNOTE: A General Message Belief Propagation Framework for Quantum Computations / Welling, Max (speaker) (University of Amsterdam)
The core computational tasks in quantum systems are the computation of expectations of operators, including reduced density matrices, and the computation of the ground state energy of a quantum system. Many tools have been developed in the literature to achieve this, including Density Functional Theory (DFT), Density Matrix Renormalization Group (DMRG) and other Tensor Network methods, Variational Monte Carlo (VMC) and so on [...]
2023 - 0:46:02. QTI other events or meetings; Quantum Techniques in Machine Learning (QTML conference 2023) External links: Talk details; Event details In : Quantum Techniques in Machine Learning (QTML conference 2023)

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2023-11-27
13:40
INVITED TALK: Topics in quantum topological data analysis / Dunjko, Vedran (speaker) (Leiden University)
Abstract: Although still a relatively niche field in classical machine learning, topological data analysis has raised substantial interest from the perspective of quantum algorithms in the last few years. In this talk we will introduce the topic of topological data analysis, and discuss the state-of-art of quantum algorithms for this problem, together with their promises and limitations, possible generalisations and connections to many-body physics..
2023 - 0:41:58. QTI other events or meetings; Quantum Techniques in Machine Learning (QTML conference 2023) External links: Talk details; Event details In : Quantum Techniques in Machine Learning (QTML conference 2023)

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2023-11-27
13:40
INVITED TALK: Accelerating Discovery in Particle Physics with AI / Ngadiuba, Jennifer (speaker) (FNAL)
The quest to understand the fundamental constituents of the universe is at the heart of particle physics. However, the complexity of particle interactions, the volume of data produced by experiments, and the intricacy of theoretical models present significant challenges to advancements in this field. [...]
2023 - 0:44:32. QTI other events or meetings; Quantum Techniques in Machine Learning (QTML conference 2023) External links: Talk details; Event details In : Quantum Techniques in Machine Learning (QTML conference 2023)

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2023-11-27
13:40
INVITED TALK: The signal and the noise: learning with random quantum circuits and other agents of chaos / QUEK, Yihui (speaker) (Harvard University)
What can we quantum-learn in the age of noisy quantum computation? Both more and less than you think. Noise limits our ability to error-mitigate, a term that refers to near-term schemes where errors that arise in a quantum computation are dealt with in classical pre-processing. [...]
2023 - 0:36:15. QTI other events or meetings; Quantum Techniques in Machine Learning (QTML conference 2023) External links: Talk details; Event details In : Quantum Techniques in Machine Learning (QTML conference 2023)

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2023-11-27
13:40
INVITED TALK: Approximate Autonomous Quantum Error Correction with Reinforcement Learning / Gneiting, Clemens (speaker) (Riken)
Quantum error correction will ultimately empower quantum computers to leverage their full potential. However, substantial device overhead and the need for frequent syndrome measurements, which are themselves error-prone, render the demonstration of logical qubits that significantly surpass break-even still challenging. [...]
2023 - 0:44:20. QTI other events or meetings; Quantum Techniques in Machine Learning (QTML conference 2023) External links: Talk details; Event details In : Quantum Techniques in Machine Learning (QTML conference 2023)

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