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Uncertainty Quantification for Learning-based Computational Imaging
Presenter
- M\u00fcjdat \u00c7etin
August 5, 2024
IMSI
AIMNet2 family of machine learning potentials: general-purpose and task-specific models for element-organic molecules and radicals, reactions and molecular crystals
Presenter
- Roman Zubatyuk
April 12, 2024
IMSI
Enforcing Structure in Scientific Machine Learning for Computational Decision Support & Digital Twins
Presenter
- Karthik Duraisamy
March 23, 2024
ICERM
Panel Discussion: Emerging Opportunities in Computational Science
Presenter
- Brian Bridges
June 9, 2023
IMSI
James Corbett - Flux: a next generation resource manager for HPC and beyond - IPAM at UCLA
Presenter
- James Corbett
May 5, 2023
IPAM
Richard Hennig & Jason Gibson - AI-driven workflows for the discovery of novel superconductors
Presenters
- Richard Hennig
- Jason Gibson
May 5, 2023
IPAM
Johannes Köster - Transparent, reproducible, and adaptable data analysis with Snakemake
Presenter
- Johannes Köster
May 4, 2023
IPAM
Johannes Blaschke - ExaFEL: Achieving real-time XFEL data analysis using Exascale Hardware
Presenter
- Johannes Blaschke
May 4, 2023
IPAM
Seshu Yamajala - Scaling NumPy applications from 1 CPU to thousands of GPUs - IPAM at UCLA
Presenter
- Seshu Yamajala
May 4, 2023
IPAM
Juliane Mueller - Adaptive Computing and multi-fidelity learning - IPAM at UCLA
Presenter
- Juliane Mueller
May 4, 2023
IPAM
Ralf Drautz - From electrons to the simulation of materials - IPAM at UCLA
Presenter
- Ralf Drautz
May 3, 2023
IPAM