CERN Accelerating science

CERN-wide meetings, trainings and events

最近の追加:
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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2023-11-23
13:40
INVITED TALK: Better than classical? The subtle art of benchmarking quantum models / Killoran, Nathan (speaker) (Xanadu)
Abstract: There is no shortage of quantum machine learning papers observing that a particular quantum model "beats its classical counterparts on real-world datasets". However, the subtlety of choices made in benchmark experiments, the small scale of the models and data, as well as narratives influenced by the commercialisation of quantum technologies carry the danger of a strong positivity bias. [...]
2023 - 0:43:08. 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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2023-11-23
12:38
StoRM / Giacomini, Francesco (speaker) (INFN CNAF) ; Vianello, Enrico (speaker) ; Cesini, Daniele (speaker) (Universita e INFN, Bologna (IT))
2023 - 0:13:25. DOMA; Data Challenge 2024 Workshop External links: Talk details; Event details In : Data Challenge 2024 Workshop

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2023-11-23
12:38
dCache / Mkrtchyan, Tigran (speaker) (DESY)
2023 - 0:19:27. DOMA; Data Challenge 2024 Workshop External links: Talk details; Event details In : Data Challenge 2024 Workshop

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2023-11-23
11:35
Area 4: A practical framework of EFT fits with published likelihoods (20'+5') / Cranmer, Kyle Stuart (speaker) (University of Wisconsin Madison (US))
Recently there has been rapid increase in the number of full statistical models (or "likelihoods") published by the experiments. Most are based on the HistFactory (pyhf) format and published in HEPData. [...]
2023 - 0:40:07. Open meetings; 6th General Meeting of the LHC EFT Working Group External links: Talk details; Event details In : 6th General Meeting of the LHC EFT Working Group

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2023-11-23
11:35
Public repository for limits on SMEFT Wilson coefficients / DAS BAKSHI, SUPRATIM (speaker) (Granada University)
2023 - 0:19:14. Open meetings; 6th General Meeting of the LHC EFT Working Group External links: Talk details; Event details In : 6th General Meeting of the LHC EFT Working Group

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2023-11-23
10:02
INVITED TALK: / Ares, Natalia (speaker) (University of Oxford)
2023 - 0:41:36. 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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