| Time |
Speaker |
Title |
| 11/03, 1:30pm |
James Halverson
(Northeastern)
Jessica N. Howard
(UCSB/KITP)
Anindita Maiti
(Perimeter Inst.)
Roger Melko
(U. Waterloo)
J. Quetzalcoatl Toledo-Marín
(TRIUMF) |
Welcome and Introductions |
| 11/04, 10:30am |
Francois Charton
Axiom - Ecole Nationale des Ponts et Chaussees |
Transformers for physics - Translators, generators and world models[Video][CC] |
| 11/04, 1:30pm |
Zohar Ringel
Hebrew Univ. |
A field theory approach to implicit bias and generalization in deep neural networks.[Video][CC] |
| 11/05, 1:30pm |
Sascha Diefenbacher
LBNL |
Unfolding with Generative and Bridge-Based Models[Video][CC] |
| 11/06, 10:30am |
Zohar Ringel
Hebrew Univ. |
Deep Learning: Some Perspectives from Physics[Video][CC] |
| 11/07, 1:30pm |
Mohamed Hibat Allah
U. Waterloo |
Recurrent neural networks for Rydberg atom arrays[Video][CC] |
| 11/10, 12:15pm |
Yi Zhuang You
UCSD |
Generative Models and Physics
[Video]
KITP Blackboard Lunch |
| 11/10, 1:30pm |
Jessica N. Howard
(UCSB/KITP)
Anindita Maiti
(Perimeter Inst.)
Javier Quetzalcoatl Toledo-Marín
(TRIUMF) |
Welcome and Introductions |
| 11/10, 2:00pm |
Lance Dixon
SLAC |
Machine Learning for Scattering Amplitudes[Slides][Video][CC] |
| 11/12, 1:30pm |
Eva Silverstein
Stanford |
Two physics-inspired architectures: Symmetry breaking in transformer training and Wilson lines as activation functions[Video][CC] |
| 11/13, 10:30am |
Wojciech Fedorko
TRIUMF |
CaloQVAE: Adding a Dash of Quantum Sauce to Generative Calorimeter Simulation[Video][CC] |
| 11/13, 11:30am |
Eliska Greplova
KIND |
Quantum Computing in the age of AI[Video][CC] |
| 11/13, 2:30pm |
Thomas Spriggs
KIND |
Equivariant Neural Wavefunctions for Lattice Gauge Theory[Slides][Video][CC] |
| 11/14, 1:30pm |
Maria Schuld
Xanadu |
Why quantum computers might be interesting for machine learning after all[Slides][Video][CC] |
| 11/17, 1:30pm |
Jessica N. Howard
(UCSB/KITP)
Anindita Maiti
(Perimeter Inst.)
J. Quetzalcoatl Toledo-Marín
(TRIUMF) |
Welcome and Introductions |
| 11/18, 10:30am |
Maximilian Swiatlowski
TRIUMF |
Examples of (Potentially Useful to You) (Generative) AI Applications in High Energy Experiment[Video][CC] |
| 11/18, 11:30am |
Javier Toledo-Marin
TRIUMF |
Symmetry breaking and hierarchical learning in RBMs[Video][CC] |
| 11/18, 1:45pm |
Ejaaz Merali
UC Davis/SJSU |
Do you even need attention?[Video][CC] |
| 11/19, 1:30pm |
Eun Ah Kim
Cornell |
To gen or not to gen[Video][CC] |
| 11/20, 10:30am |
Agnes Valenti
Flatiron Institute |
How smart should neural-network quantum states be?[Video][CC] |
| 11/20, 11:30am |
David Shih
Rutgers |
GenAI for Anomaly Detection at LHC and Beyond[Video][CC] |
| 11/21, 10:30am |
Vishnu Jejjala
Wits University |
Precision String Phenomenology[Slides][Video][CC] |
| 11/21, 1:30pm |
Michael Albergo
Harvard |
Overview on dynamical transport generative models: new frontiers and applications[Embargoed] |
| 11/24, 1:30pm |
Jessica N. Howard
(UCSB/KITP)
Anindita Maiti
(Perimeter Inst.)
J. Quetzalcoatl Toledo-Marín
(TRIUMF) |
Welcome and Introductions |
| 11/24, 2:00pm |
Anna Dawid
Leiden Univ. |
Curious loss landscapes of neural networks[Video][CC] |
| 11/25, 10:30am |
Matija Medvidovic
ETH Zurich |
Adiabatic transport of neural network quantum states[Video][CC] |
| 11/25, 11:30am |
Yitian Sun
McGill Univ. |
Inference Generative models and the Galactic Center gamma-ray Excess[Video][CC] |
| 12/01, 1:30pm |
Jessica N. Howard
(UCSB/KITP)
Anindita Maiti
(Perimeter Inst.)
Roger Melko
(U. Waterloo)
J. Quetzalcoatl Toledo-Marín
(TRIUMF) |
Welcome and Introductions |
| 12/02, 10:30am |
Liang Fu
MIT |
Discovering new quantum phases with fermionic neural network[Video][CC] |
| 12/03, 10:30am |
Daniel Hackett
Fermilab |
AI/ML for lattice quantum field theory[Video][CC] |
| 12/03, 1:30pm |
Eliska Greplova
(KIND)
Maria Schuld
(Xanadu)
Yi Zhuang You
(UCSD) |
Discussion |
| 12/04, 10:30am |
Ayodele Ore
Universitaet Heidelberg |
Fitting neural models of hadronization[Video][CC] |
| 12/04, 11:30am |
Estelle Inack
Perimeter Inst. |
Generative Al for High & Low Energy Physics[Video][CC] |
| 12/08, 1:30pm |
Jessica N. Howard
(UCSB/KITP)
Anindita Maiti
(Perimeter Inst.)
Roger Melko
(U. Waterloo)
J. Quetzalcoatl Toledo-Marín
(TRIUMF) |
“Welcome and Introductions” |
| 12/08, 1:45pm |
Marina Marinkovic
ETH Zurich |
What is difficult in simulating Lattice Gauge Theories and how ML methods can help?[Video][CC] |
| 12/09, 10:30am |
Gregor Kasieczka
Univ. Hamburg |
Agents, Surrogates, and Foundation Models: Rethinking Particle Physics with GenAI[Video][CC] |
| 12/09, 2:00pm |
Savannah Thais
Hunter College |
Good AI for Physics Needs AI Ethics and Good AI Ethics Needs Physics[Video][CC] |
| 12/09, 3:00pm |
James Osborn
Argonne |
Some Use Cases for AI/ML in Lattice Field Theory Simulations[Video][CC] |
| 12/10, 1:30pm |
Savannah Thais
Hunter College |
Discussion |
| 12/11, 10:30am |
Koji Hashimoto
Kyoto Univ. |
Holography, QCD and neural networks[Video][CC] |
| 12/11, 11:15am |
William Detmold
MIT |
Machine Learning Contour Deformations for Lattice Field Theory[Video][CC] |
| 12/11, 1:45pm |
Ying Jer Kao
NTU |
Synergy of Tensor Networks and Variational Quantum Circuits for Quantum Machine Learning[Video][CC] |
| 12/11, 2:45pm |
Peter Boyle
BNL |
Field Transformation Hybrid Monte Carlo (+ Agentic workflow baby steps)[Video][CC] |
| 12/12, 10:30am |
Mathis Gerdes
Univ. of Amsterdam |
Generation with Unified Diffusion - RG inspired Diffusion Models[Video][CC] |
| 12/12, 1:30pm |
Richard Scalettar
UC Davis |
Quantum Simulation in Condensed Matter Physics: Connections to Lattice Gauge Theory and what we want from Artificial Intelligence[Video][CC] |
| 12/15, 1:30pm |
James Halverson
(Northeastern)
Jessica N. Howard
(UCSB/KITP)
Anindita Maiti
(Perimeter Inst.)
Roger Melko
(U. Waterloo)
J. Quetzalcoatl Toledo-Marin
(TRIUMF) |
Welcome and Introductions |
| 12/15, 1:45pm |
Anna Golubeva
Zyphra |
What matters at scale |
| 12/16, 10:30am |
Sebastian Wetzel
U. Waterloo |
Retrieving physical concepts learned by artificial neural networks[Video][CC] |
| 12/16, 11:30am |
Sung Hak Lim
IBS Korea |
Understanding Galactic Dark Matter with Generative Models[Video][CC] |
| 12/17, 10:30am |
Cengiz Pehlevan
Harvard |
Scaling Neural Networks: Laws, Limits, and Implications |
| 12/17, 1:30pm |
Aishik Ghosh
Georgia Tech |
Unlocking statistical inference in high-dimensions with reliable uncertainty quantification for particle physics |
| 12/18, 10:00am |
Yi Zhuang You
UCSD |
How Focused are LLMs? |
| 12/18, 11:30am |
James Halverson
(Northeastern)
Jessica N. Howard
(UCSB/KITP)
Anindita Maiti
(Perimeter Inst.)
Roger Melko
(U. Waterloo)
J. Quetzalcoatl Toledo-Marin
(TRIUMF) |
Closing remarks |
