Country: Germany or United States of America
and
Keywords: Graph Neural Networks or neutron or NFDI
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Magnetic Structure Determination from Neutron Diffraction Data (MagStr)
3 - 7 October 2022
Oak Ridge, United States of America
Magnetic Structure Determination from Neutron Diffraction Data (MagStr) https://conference.sns.gov/event/339/ https://pan-training.eu/events/magnetic-structure-determination-from-neutron-diffraction-data-magstr The school will provide hands-on training and lectures on how to determine magnetic structures from powder and single-crystal neutron data. The techniques and theory of representational analysis and magnetic space groups will be introduced by leading experts and demonstrated in a series of hands-on examples. The format will follow past workshops. But this year it is back to in-person student attendance! Lectures and hands-on tutorial sessions will cover: 1. Symmetry analysis using representation theory and the SARAh program and ISOTROPY Suite 2. Magnetic space groups using the Bilbao Crystallographic Server 3. Refinement strategies using the FullProf Suite, GSAS-II and Jana 4. Magnetic structure determination from powder and single-crystal data The school is intended for graduate students, postdocs, and research scientists who have a working knowledge of crystallographic refinement and will benefit from incorporating the techniques of magnetic structure determination from neutron diffraction into their research. 2022-10-03 09:00:00 UTC 2022-10-07 17:00:00 UTC Third Street, Oak Ridge, United States of America Third Street Oak Ridge Roane County United States of America neutron diffraction Oak Ridge National Laboratory Stuart Calder (caldersa@ornl.gov) Ovidiu Garlea (garleao@ornl.gov) Huibo Cao (caoh@ornl.gov) Clarina dela Cruz (delacruzcr@ornl.gov) [] graduate studentspostdocsresearch scientists workshops_and_courses [] neutronORNL -
DAPHNE4NFDI Annual Meeting 2023
3 - 5 April 2023
Hamburg, Germany
DAPHNE4NFDI Annual Meeting 2023 https://events.hifis.net/event/601/ https://pan-training.eu/events/daphne4nfdi-annual-meeting-2023 The DAPHNE4NFDI Annual Meeting 2023 will take place at DESY, Hamburg from Monday, April 3rd to Wednesday, April 5th 2023. DAPHNE4NFDI members are welcome to join us for all sessions and activities on all three days. DAPHNE4NFDI participants are cordially invited to join us on Tuesday afternoon and Wednesday. This meeting lives from your contributions! We therefore encourage you to submit an abstract for a poster (required for DAPHNE4NFDI members) or oral presentation. Please see the Call for abstracts page for more information. 2023-04-03 14:00:00 UTC 2023-04-05 15:30:00 UTC Blomkamp, Hamburg, Germany Blomkamp Hamburg Germany 22607 DESY [] PaN CommunityPaN users [] [] DAPHNENFDIphotonneutron -
Deep Learning School
21 - 24 May 2024
Filderstadt, Germany
Deep Learning School https://indico.desy.de/event/40560/ https://pan-training.eu/events/deep-learning-school-46deca27-6b8d-4b37-bbe7-5c5e63ad2197 The Active Training Course "Advanced Deep Learning" is hosted over 4 days at (location tba) by the community organization DIG-UM with support from the BMBF-funded ErUM-Data-Hub. The event serves the professional education of young scientists belonging to the ErUM Community. The intensive course on Graph Neural Networks, Transformers, Normalizing Flows and Autoencoders will be held from 21.05.24 - 24.05.24. The course includes a challenge to be worked out and presented by participant subgroups. The workshop is aimed at deep-learning enthusiasts from all ErUM communities (Research on Universe and Matter) who have prior knowledge of neural networks and applied basic concepts of deep learning. A fee of 300€ will be charged for participation in the course. The workshop fee includes the cost of the workshop, accommodation and catering. Registration closes tba. 2024-05-21 17:00:00 UTC 2024-05-24 14:00:00 UTC ErUM-Data-Hub (BMBF) Bernhäuser Forst, Filderstadt, Germany Bernhäuser Forst Filderstadt Germany 70794 [] [] [] workshops_and_courses [] Graph Neural NetworksAutoencoderModel DiffusionNormalizing Flows

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