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David Bortz - Weak form SciML for Learning Models on Different Scales - IPAM at UCLA
Presenter
- David Bortz
October 7, 2025
IPAM
Adityanarayanan Radhakrishnan - How do neural networks learn features from data? - IPAM at UCLA
Presenter
- Adityanarayanan Radhakrishnan
October 18, 2024
IPAM
Roger Melko - Language Models for Quantum Simulation - IPAM at UCLA
Presenter
- Roger Melko
October 20, 2023
IPAM
Roman Grigoriev - Bridging scales using physically-informed machine learning - IPAM at UCLA
Presenter
- Roman Grigoriev
October 10, 2025
IPAM
Mohammed AlQuraishi - OpenFold: Lessons and insights from rebuilding and retraining AlphaFold2
Presenter
- Mohammed AlQuraishi
January 23, 2023
IPAM
Marika Maria Kieferova - Generating Approx. Ground State of Molecules Using Quantum Machine Learning
Presenter
- Marika Kieferova
October 18, 2023
IPAM
Shenglin Huang - Data-Driven Model Discovery for Non-equilibrium Processes - IPAM at UCLA
Presenter
- Shenglin Huang
April 18, 2023
IPAM
Recent Advances in Recommender Systems and Future Directions
Presenter
- George Karypis
March 22, 2016
IMA
Gabor Csányi - Machine learning potentials: from polynomials to message passing networks
Presenter
- Gabor Csányi
April 17, 2023
IPAM
Leena Vankadara - Scaling Insights from Infinite-Width Theory for Next Gen Architecture & Learning
Presenter
- Leena Vankadara
October 18, 2024
IPAM
Huan Lei - Energy-stable machine-learning model of non-Newtonian hydrodynamics w/ molecular fidelity
Presenter
- Huan Lei
October 8, 2025
IPAM
Maria Schuld - How to rethink quantum machine learning - IPAM at UCLA
Presenter
- Maria Schuld
October 16, 2023
IPAM