Machine Learning and the Renormalization Group
from
Monday 27 May 2024 (08:30)
to
Friday 31 May 2024 (23:45)
Monday 27 May 2024
08:30
08:30 - 09:30
Room: Aula Renzo Leonardi
09:30
09:30 - 09:45
Room: Aula Renzo Leonardi
09:45
09:45 - 10:15
Room: Aula Renzo Leonardi
10:15
10:15 - 11:00
Room: Aula Renzo Leonardi
Contributions
10:15
Non-perturbative renormalization for the neural network-QFT correspondence
-
Harold Erbin
(
CEA-IPHT
)
11:00
11:00 - 11:30
Room: Aula Renzo Leonardi
11:30
11:30 - 12:15
Room: Aula Renzo Leonardi
Contributions
11:30
Physics-induced functional RG flows
-
Friederike Ihssen
(
Universität Heidelberg
)
12:15
12:15 - 12:30
Room: Aula Renzo Leonardi
12:30
12:30 - 14:30
Room: Aula Renzo Leonardi
14:30
14:30 - 15:15
Room: Aula Renzo Leonardi
Contributions
14:30
Extracting operator content of quantum and classical lattice models using lossy compression theory
-
Maciej Koch-Janusz
(
Haiqu, Inc.
)
15:15
15:15 - 15:45
Room: Aula Renzo Leonardi
15:45
15:45 - 16:30
Room: Aula Renzo Leonardi
Contributions
15:45
ML through the lens of Renormalization Group
-
Anindita Maiti
(
Perimeter Institute for Theoretical Physics
)
16:30
16:30 - 17:00
Room: Aula Renzo Leonardi
17:30
17:30 - 18:30
Room: Villa Tambosi
Tuesday 28 May 2024
09:30
09:30 - 11:00
Room: Aula Renzo Leonardi
Contributions
09:30
Soft matter physics as a joint between deep learning and renormalisation group
-
Raffaello Potestio
(
UniTn - Physics Dept.
)
10:15
Generating configurations of increasing lattice size with machine learning and the inverse renormalization group
-
Dimitrios Bachtis
(
ENS Paris
)
11:00
11:00 - 11:30
Room: Aula Renzo Leonardi
11:30
11:30 - 12:15
Room: Aula Renzo Leonardi
Contributions
11:30
Detecting composite orders in layered models via machine learning
-
Nicolo Defenu
(
ETH Zurich
)
12:15
12:15 - 12:30
Room: Aula Renzo Leonardi
12:30
12:30 - 14:30
Room: Aula Renzo Leonardi
14:30
14:30 - 15:15
Room: Aula Renzo Leonardi
Contributions
14:30
Renormalization Group Approach for Machine Learning Hamiltonian
-
Misaki Ozawa
(
Univ. Grenoble Alpes, France
)
15:15
15:15 - 15:45
Room: Aula Renzo Leonardi
15:45
15:45 - 16:30
Room: Aula Renzo Leonardi
Contributions
15:45
Phi^4 Theory as a Neural Network Field Theory
-
Jim Halverson
(
Northeastern University
)
16:30
16:30 - 17:00
Room: Aula Renzo Leonardi
Wednesday 29 May 2024
09:30
09:30 - 11:00
Room: Aula Renzo Leonardi
Contributions
09:30
Machine learning renormalization group actions
-
Kieran Holland
(
University of the Pacific
)
Urs Wenger
10:15
Machine learning renormalization group actions
-
Kieran Holland
(
University of the Pacific
)
Urs Wenger
11:00
11:00 - 11:30
Room: Aula Renzo Leonardi
11:30
11:30 - 12:15
Room: Aula Renzo Leonardi
Contributions
11:30
Localized machine learned flow maps to accelerate Markov Chain Monte Carlo simulations
-
Jacob Finkenrath
12:15
12:15 - 12:30
Room: Aula Renzo Leonardi
12:30
12:30 - 14:30
Room: Aula Renzo Leonardi
14:30
14:30 - 15:15
Room: Aula Renzo Leonardi
Contributions
14:30
Applications of flow models to the generation of correlated lattice QCD ensembles
-
Fernando Romero-Lopez
(
MIT
)
15:15
15:15 - 15:45
Room: Aula Renzo Leonardi
15:45
15:45 - 16:30
Room: Aula Renzo Leonardi
Contributions
15:45
Understanding infinite width neural networks from the perspective of statistical mechanics
-
Jascha Sohl-Dickstein
(
Anthropic
)
16:30
16:30 - 17:00
Room: Aula Renzo Leonardi
Thursday 30 May 2024
09:30
09:30 - 11:00
Room: Aula Renzo Leonardi
Contributions
09:30
Effective Theory of Deep Neural Networks
-
Sho Yaida
(
Meta Platforms, Inc.
)
10:15
Diffusion Models as Stochastic Quantization in Lattice Field Theory
-
Kai Zhou
(
Frankfurt Institute for Advanced Studies
)
11:00
11:00 - 11:30
Room: Aula Renzo Leonardi
11:30
11:30 - 12:15
Room: Aula Renzo Leonardi
Contributions
11:30
Renormalizing Diffusion Models
-
Semen Rezchikov
(
Princeton University / Institute of Advanced Study
)
12:15
12:15 - 12:30
Room: Aula Renzo Leonardi
12:30
12:30 - 14:30
Room: Aula Renzo Leonardi
14:30
14:30 - 15:15
Room: Aula Renzo Leonardi
Contributions
14:30
RG inspired perspectives on diffusion models
-
Mathis Gerdes
(
University of Amsterdam
)
15:15
15:15 - 15:45
Room: Aula Renzo Leonardi
15:45
15:45 - 16:30
Room: Aula Renzo Leonardi
Contributions
15:45
Topological Data Analysis of Monopoles in U(1) Lattice Gauge Theory
-
Xavier Crean
(
Swansea University
)
16:30
16:30 - 17:00
Room: Aula Renzo Leonardi
20:00
20:00 - 22:00
Room: Ristorante Scrigno del Duomo
Friday 31 May 2024
09:30
09:30 - 11:00
Room: Aula Renzo Leonardi
Contributions
09:30
Action estimation with continuous-mixture autoregressive networks
-
Lingxiao Wang
(
RIKEN
)
10:15
Learning correlations between "characters" by a nano-GPT
-
Ouraman Hajizadeh
11:00
11:00 - 11:30
Room: Aula Renzo Leonardi
11:30
11:30 - 12:15
Room: Aula Renzo Leonardi
Contributions
11:30
Learning and (not quite) random matrix theory
-
Gert Aarts
(
Swansea University
)
12:15
12:15 - 12:30
Room: Aula Renzo Leonardi
12:30
12:30 - 14:30
Room: Aula Renzo Leonardi
14:30
14:30 - 15:15
Room: Aula Renzo Leonardi
15:15
15:15 - 15:45
Room: Aula Renzo Leonardi
15:45
15:45 - 16:00
Room: Aula Renzo Leonardi