Name: Machine Learning approaches in Lattice QCD - An interdisciplinary exchange
Start: 2023-02-27T08:00:00+01:00
End: 2023-03-03T20:00:00+01:00
Location: Institute for Advanced Study of the Technische Universität München

Machine Learning approaches in Lattice QCD - An interdisciplinary exchange

from Monday, February 27, 2023 (8:00 AM) to Friday, March 3, 2023 (8:00 PM)

Monday, February 27, 2023

8:00 AM Welcome
Welcome
8:00 AM - 8:20 AM
9:00 AM Machine learning is ubiquitous - Maria-Paola Lombardo
Machine learning is ubiquitous
- Maria-Paola Lombardo
9:00 AM - 9:30 AM
10:00 AM
10:00 AM - 10:45 AM
Contributions

10:00 AM Aspects of scaling and scalability for flow-based samplers - Daniel Hackett

10:25 AM Learning trivializing flows - David Albandea
10:45 AM Coffee break
Coffee break
10:45 AM - 11:15 AM
11:15 AM
11:15 AM - 1:00 PM
Contributions

11:15 AM Fourier-Flow model generating Feynman paths - Lingxiao Wang

11:35 AM Conditional Normalizing Flow model for sampling in the Critical region of Lattice Field Theory - Ankur Singha

11:55 AM Numerical calculation of the color flux tube thickness using continuous normalizing flows - Elia Cellini

12:15 PM Panel discussion
1:00 PM Lunch
Lunch
1:00 PM - 2:30 PM

2:30 PM

2:30 PM - 4:00 PM

4:00 PM Coffee break
Coffee break
4:00 PM - 4:30 PM
4:30 PM Contour deformation methods for noise reduction
Contour deformation methods for noise reduction
4:30 PM - 6:00 PM
Contributions

4:30 PM Signal-to-noise improvement with contour deformations - Michael Wagman

4:50 PM Complex normalizing flows and subtractions for sign problems - Yukari Yamauchi

5:10 PM Applying Complex Valued Neural Networks to the Hubbard Model Sign Problem: A Survey and Case Study - Marcel Rodekamp

5:30 PM Panel discussion - Gurtej Kanwar Thomas Luu Will Detmold
Tuesday, February 28, 2023
9:00 AM ML for particle physics - Lukas Heinrich
ML for particle physics
- Lukas Heinrich
9:00 AM - 9:30 AM
10:00 AM How to accelerate gauge field field generation using flow-based and hybrid models - Phiala Shanahan
How to accelerate gauge field field generation using flow-based and hybrid models
- Phiala Shanahan
10:00 AM - 10:30 AM
10:45 AM Coffee break
Coffee break
10:45 AM - 11:15 AM
11:15 AM
11:15 AM - 1:00 PM
Contributions

11:15 AM Simulation of the 2D Schwinger Model via machine-learned flows in Global Correction steps - Jacob Finkenrath

11:40 AM Variational Autoregressive Networks for Information Theory - Tomasz Stebel

12:00 PM Machine-learning-assisted Monte Carlo fails at sampling computationally hard problems - Jeanne Trinquier

12:20 PM Panel discussion
1:00 PM Lunch
Lunch
1:00 PM - 2:30 PM

2:30 PM

2:30 PM - 4:00 PM

4:00 PM Coffee break
Coffee break
4:00 PM - 4:30 PM
4:30 PM
4:30 PM - 6:00 PM
Contributions

4:30 PM Brief introduction on spectral functions and their computation - Gert Aarts

4:40 PM Spectral reconstruction with Gaussian processes - Julian Urban

5:10 PM Spectral reconstruction with neural networks - Kai Zhou Lingxiao Wang

5:40 PM Learning regulators for spectral reconstruction - Alexander Rothkopf

5:50 PM Panel discussion
Wednesday, March 1, 2023
9:00 AM
9:00 AM - 10:40 AM
Contributions

9:00 AM Learning Trivializing Gradient Flows - Simone Bacchio

9:40 AM An analysis of Bayesian estimates for missing higher orders in perturbative calculations - Aleksas Mazeliauskas

10:10 AM Deep Learning and the Standard Model: a philosophy of science perspective - Luigi Scorzato
10:40 AM Coffee break
Coffee break
10:40 AM - 11:10 AM
11:10 AM
11:10 AM - 1:00 PM
Contributions

11:10 AM Generative models and EFTs - Marina Marinkovic
1:00 PM Lunch
Lunch
1:00 PM - 2:30 PM
2:30 PM
2:30 PM - 4:30 PM
Contributions

2:30 PM Building Transport Maps and Making Good Use of Them - Michael Albergo

3:00 PM Automatic differentiation for Lattice QCD - A. Ramos

3:20 PM TBA - Miles Cranmer

3:50 PM Panel discussion
4:30 PM Reception
Reception
4:30 PM - 6:00 PM
6:00 PM Provably exact: AI and theoretical physics - Phiala Shanahan
Provably exact: AI and theoretical physics
- Phiala Shanahan
6:00 PM - 7:00 PM
Thursday, March 2, 2023
9:00 AM ML and quantum field theories - Gert Aarts
ML and quantum field theories
- Gert Aarts
9:00 AM - 9:30 AM
9:45 AM
9:45 AM - 10:45 AM
Contributions

10:00 AM Complex Langevin real-time simulations and ML - Alexander Rothkopf

10:25 AM Towards fully bayesian analyses in Lattice QCD - Julien Frison
10:45 AM Coffee Break
Coffee Break
10:45 AM - 11:15 AM
11:15 AM
11:15 AM - 1:00 PM
Contributions

11:15 AM Physical Concepts from Neural Networks with Two Inputs - Sebastian Wetzel

11:35 AM Ab-Initio Quantum Chemistry via Graph Neural Networks - Nicholas Gao

12:00 PM Panel discussion on ML for physics interpretation
1:00 PM Lunch
Lunch
1:00 PM - 2:30 PM

2:30 PM

2:30 PM - 4:00 PM

4:00 PM Coffee break
Coffee break
4:00 PM - 4:30 PM

4:30 PM

4:30 PM - 6:00 PM
Friday, March 3, 2023
9:00 AM Model-Independent Learning of Quantum Phases of Matter with Quantum Convolutional Neural Networks - Frank Pollmann
Model-Independent Learning of Quantum Phases of Matter with Quantum Convolutional Neural Networks
- Frank Pollmann
9:00 AM - 9:30 AM
9:30 AM
9:30 AM - 10:45 AM
Contributions

9:30 AM Machine learning hadron spectral functions in Lattice QCD - Gabor Papp

10:00 AM TBA - Gitta Kutyniok
10:45 AM Coffee break
Coffee break
10:45 AM - 11:15 AM

11:15 AM

11:15 AM - 1:00 PM

1:00 PM Lunch
Lunch
1:00 PM - 2:30 PM

2:30 PM

2:30 PM - 4:00 PM

4:00 PM Coffee break
Coffee break
4:00 PM - 4:30 PM

6:00 PM Workshop ending
Workshop ending
6:00 PM - 6:20 PM