Maxim Ziatdinov - Bits And Atoms: Exploring The Intersection Of Machine Learning And Microscopy

Maxim Ziatdinov - Bits and Atoms: Exploring the Intersection of Machine Learning and Microscopy

Institute for Pure & Applied Mathematics (IPAM)

ML_EM_02_Introduction_to_EM

Machine Learning in the Nanoworld

ICN2 Manuel Cardona Lecture: Bits to Atoms and Atoms to Bits (Prof. Sergei V. Kalinin)

Institut Català de Nanociència i Nanotecnologia

Rama Vasudevan - Advancing Microscopy with Machine Learning: Lessons from Scanning Probe Microscopy

Institute for Pure & Applied Mathematics (IPAM)

Deep learning for atomically resolved imaging techniques

Berkeley Institute for Data Science (BIDS)

Accelerating Scientific Discovery with Machine Learning | J. Nathan Kutz | TEDxUofW

George Barbastathis - On the use of machine learning for computational imaging - IPAM at UCLA

Institute for Pure & Applied Mathematics (IPAM)

Stefan Chmiela - Accurate global machine learning force fields for molecules with hundreds of atoms

Institute for Pure & Applied Mathematics (IPAM)

Peter Binev - Modeling in Electron Microscopy - IPAM at UCLA

Institute for Pure & Applied Mathematics (IPAM)

Machine Learning Fundamentals: Bias and Variance

StatQuest with Josh Starmer

Transmission Electron Microscope

Biomedical Imaging Unit - Southampton