Artificial Intelligence Applied to Photon and Neutron Science

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Wine & Cheese buffet and Poster Session - in ESRF entrance hall and mezzanine

Morning 1

Morning 2

Afternoon 1

Afternoon 2

Coffee Break

Discussion

Lunch

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Contributions*

Applications of Artificial Neural Networks in Electron Microscopy (in session "Morning 2")

Big Data Science Center at the Shanghai Synchrotron Radiation Facility - The first Superfacility Platform in China (in session "Afternoon 2")

Biomedical image reconstruction: From the foundations to deep neural networks (in session "Morning 1")

Convolutional neural networks for DESY photon science (in session "Afternoon 2")

Data-driven Materials Discovery for Functional Applications (in session "Morning 2")

Deep Generative Models for detector simulation (in session "Morning 1")

Deep learning for classifying and sorting diffraction images (in session "Morning 2")

Deep learning for small angle scattering under grazing incidence (in session "Afternoon 2")

Deep learning for Synchrotron X-ray Imaging (in session "Morning 1")

Deriving the big picture from huge spatial datasets: How to make a little training data go a long way (in session "Morning 1")

DOE's Center for Advanced Mathematics for Energy Research Applications (CAMERA): Artificial Intelligence, Machine Learning, and Experimental Facilities: Present and Future (in session "Afternoon 2")

Improving data analysis using artificial intelligence: an ESRF perspective (in session "Afternoon 1")

Introduction to Machine Learning and Deep Neural Networks for scattering science (in session "Afternoon 1")

Machine learning accelerated analysis of materials data: The Smart facility (in session "Morning 2")

Machine learning algorithms for image processing in CryoEM (in session "Afternoon 2")

Machine learning and artificial intelligence in MX (in session "Afternoon 2")

Machine learning applications for Small Angle X-ray Scattering data collection and analysis at EMBL-Hamburg (in session "Afternoon 1")

Machine Learning at Argonne National Lab (in session "Afternoon 1")

Machine Learning at Diamond Light Source: Past, Present and Future (in session "Afternoon 2")

Machine Learning at ILL (in session "Afternoon 2")

Machine Learning for accelerating understanding from Neutron Scattering Data (in session "Afternoon 2")

Machine learning for an XFEL accelerator (in session "Afternoon 1")

Machine Learning for improving image quality in tomography (in session "Morning 1")

Machine Learning for Spectroscopy: From Spectra to Atomic Structures (in session "Morning 2")

PyFitit: the software for quantitative analysis of XANES spectra using machine-learning algorithms (in session "Morning 2")

Scientific Machine Learning Benchmarks (in session "Afternoon 1")

Towards automated analysis for neutron reflectivity (in session "Afternoon 2")

Welcome from ESRF Director (in session "Afternoon 1")

Welcome from ILL Director (in session "Afternoon 1")

What does artificial intelligence see in 3D protein structures? (in session "Morning 1")

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12/11/2019

13/11/2019

14/11/2019

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