Machine Learning in Natural Sciences: from Quantum Physics to Nanoscience and Structural Biology

Session

Community Competitions

19 Sept 2022, 14:45

Seminarraum 1-3 (CFEL (Building 99))

40. Creating community driven challenges to advance Science

Dr Gorka Muñoz-Gil (University of Innsbruck)

19/09/2022, 14:45

Invited Talk

In this talk, I will present the Anomalous Diffusion (AnDi) challenge, a community driven event aimed at pushing our understanding of diffusion phenomena. Deviations from Brownian motion leading to anomalous diffusion are found in transport dynamics from quantum physics to life sciences. The characterization of anomalous diffusion from the measurement of an individual trajectory is a...

19. Unraveling heterogeneous diffusion in single particle trajectories

Mr Borja Requena (ICFO-The Institute of Photonic Sciences)

19/09/2022, 15:30

Community Competitions

Contributed Talk (15 min)

We propose a machine learning method to characterize heterogeneous diffusion processes at a single-step level. The machine learning model takes a trajectory of arbitrary length as input and outputs the prediction of a property of interest, such as the diffusion coefficient or the anomalous exponent, at every time step. This way, changes in the diffusive properties along the trajectory emerge...