A deep dive into the mathematics of Machine Learning
Crash course on Machine Learning
Keywords: machine learning
Resource type: slides
A deep dive into the mathematics of Machine Learning
https://indico.desy.de/event/33127/contributions/117087/attachments/71317/91043/user_meeting_ml_intro_jan_2022.pdf
https://pan-training.eu/materials/a-deep-dive-into-the-mathematics-of-machine-learning
Crash course on Machine Learning
machine learning
research data scientist
masters students
PhD students
Machine learning in electronic-structure theory
Machine Learning approaches are increasingly being used across many fields of science, with electronic structure theory being no exception. They offer novel approaches to age-old problems. In recent years they have been used in construction of trial wavefunctions, in computing Hamiltonians, and...
Keywords: machine learning, electronic-structure theory
Resource type: video
Machine learning in electronic-structure theory
https://www.youtube.com/watch?v=Sgp0w74k9kQ
https://pan-training.eu/materials/machine-learning-in-electronic-structure-theory
Machine Learning approaches are increasingly being used across many fields of science, with electronic structure theory being no exception. They offer novel approaches to age-old problems. In recent years they have been used in construction of trial wavefunctions, in computing Hamiltonians, and in direct calculation of properties and forces.
These methods are highly versatile and computationally efficient, yet many questions regarding their interpretability and ability to extrapolate information remains unanswered.
How are they being used in electronic structure theory today, and how do they fit into the bigger picture? Would electronic structure theory have looked anything different if it was conceived in the age of machine learning? This seminar seeks to answer these kinds of questions, and was originally given as a trial lecture at the Hylleraas Centre of Quantum Molecular Sciences at the University of Oslo.
machine learning, electronic-structure theory
Machine Learning-based Spectra Classification
Yue Sun presents: Machine Learning-based Spectra Classification at the 2nd PaNOSC and ExPaNDS PaN EOSC Symposium (October 2021).
Scientific topics: spectroscopy
Keywords: machine learning, XFEL, FAIR, large dataset, NeXus, spectroscopy, wp5-ExPaNDS
Resource type: video, slides
Machine Learning-based Spectra Classification
https://zenodo.org/record/5636331/files/20211026-PaN-EOSC-Symposium2021-YueSun-UseCase.pdf?download=1
https://pan-training.eu/materials/machine-learning-based-spectra-classification
Yue Sun presents: Machine Learning-based Spectra Classification at the 2nd PaNOSC and ExPaNDS PaN EOSC Symposium (October 2021).
spectroscopy
machine learning, XFEL, FAIR, large dataset, NeXus, spectroscopy, wp5-ExPaNDS
PaN Community
scientists