Machine Learning Coffee Morning Seminar Series
Upcoming Talks
This is an occasional and informal series of meetings on topics related to Machine Learning in Nuclear, Atomic and Molecular Physics, usually held in the NDS Library (Room A23-34) and sometimes online.
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11am Date TBC
Georg SCHNABEL: Nuclear data for everyone: converting ENDF files to JSON and back
Previous Talks
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11 am Thursday 3 November 2022
Arjan KONING: Nuclear model parameter optimization with TALYS
[presentation [pdf]]
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11 am Thursday 10 November 2022
Christian HILL and DIPTI: CollisionDB and ALADDIN2: plasma collisional data format, validation and API
[presentation [pdf]]
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11 am Thursday 24 November 2022
Ludmila MARIAN: Discussion session on software and data licensing
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10 am Wednesday 14 December 2022, Room A23-11
Ludmila MARIAN: JupyterHub: a solution for running remote technical workshops
In the last few years, events have been transformed from in-person to online. This includes technical workshops, where the participants are expected to gain hands-on experience using scientific software tools and methods presented in the lectures.
The Atomic and Molecular Data Unit (AMD Unit) ran one of these workshops last year, the Joint ICTP-IAEA Virtual Workshop on Atomistic Modelling of Radiation Damage in Nuclear Systems (4 – 8 October 2021), and successfully used JupyterHub as an online teaching platform, engaging participants in technical exercises.
This talk will present JupyterHub in general, and the setup used for this ICTP workshop, in particular.
[presentation [pdf]]
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11 am Thursday 12 January 2023
Georg SCHNABEL: Modelling nuclear data relationships with Bayesian networks
[presentation [pdf]]
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11am Thursday 26 January 2023, Room A23-11
Marco VERPELLI: NDLab : virtual experiments with nuclear data. A Python toolkit enabling the use of AI algorithms
For a preview, take a look at this short YouTube video. The software can be downloaded from its GitHub repository.
[presentation [pdf]]
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11am Friday 17 February 2023, Room A23-11
Viktor Zerkin: EE-View: Experimental-Evaluated Data Viewer. Overview, Technical Details and Demo
[presentation [pdf]]
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10am 27 April 2023
All present: Discussion on Large Language Models (LLMs)