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

Session

Infrastructure and Best Practices

IBP

22 Sept 2022, 11:00

Seminarraum 1-3 (CFEL (Building 99))

52. Machine-learning from heterogenous data: dream or reality?

Prof. Claudia Draxl (Humboldt Universität)

22/09/2022, 11:00

Invited Talk

Veracity (uncertainty of data quality) and variety (heterogeneity of form and meaning of data) are two of the 4V challenges of Big Data. Both are issues for the FAIRness of materials-science results, concerning in particular, the interoperability, i.e., the “I” in FAIR. I will address what may enable us to use heterogenous data for machine learning, e.g. data from different sources or...

18. Tackling Multimodal Device Distributions in Inverse Photonic Design: Lessons learned from Invertible Neural Networks

Michel Frising (Universidad Autonoma de Madrid)

22/09/2022, 11:45

Infrastructure and Best Practices

Contributed Talk (15 min)

Inverse design problems in photonics typically operate in very high dimensional parameter spaces which are notoriously difficult to navigate to find local or global optima. Even worse, from practice it is known that different devices can have comparable performance leading to multimodal device distributions. This often confuses optimization routines causing oscillations and failure to...