2 QLS Seminars - Thu. 26 June at 10h00 and 11h00

[Quantitative Life Sciences]

Dear All,

On *Thursday, 26 June _at 10:00_ *CET, Dr. Junghyo Jo (Seoul National 
University) will give a seminar titled:

*"**An introduction to diffusion models in generative machine learning**"

*_Abstract:

_Diffusion models are a class of generative models in machine learning 
that iteratively transform data into noise through a forward diffusion 
process, typically converging toward a Gaussian distribution. A 
corresponding reverse process then reconstructs data-like samples by 
denoising these vectors step-by-step. This pair of processes resembles 
coarse-graining and fine-graining operations. In this talk, I will 
provide a brief introduction to the principles and mechanics of 
diffusion models, focusing on how they generate realistic samples from 
noise.*


_At 11:00_ *CET, Prof. Michael Chertkov (University of Arizona) will 
give a seminar titled:
*
"Non-Equilibrium Statistical Mechanics of/for AI"

*_Abstract:_*

*This talk presents a unifying applied mathematics/theoretical physics 
framework that bridges core components of modern generative AI -- 
diffusion models, reinforcement learning, and transformers -- through 
the lens of contemporary applied mathematics. Central to this framework 
are the concepts of Decision Flows and Path Integral Diffusions, which 
offer structured approaches to sequential sampling over discrete, 
continuous, and hybrid spaces. These approaches are rooted in 
Green-function-based control, Schrödinger bridges, and non-equilibrium 
statistical physics.

Building on recent work, we explore analytically tractable and 
algorithmically efficient regimes -- often requiring minimal use of 
neural networks -- where sampling from complex distributions becomes 
both explainable and extrapolative. We highlight connections between 
score-based diffusion, linearly-solvable Markov Decision Processes, and 
energy-based models, including emerging insights into phase transitions 
in generative AI (e.g., memorization and speciation dynamics).

Applications span inference/sampling in Ising models, CIFAR-10 image 
generation, physics-informed reinforcement learning in turbulent flows, 
and auto-regressive modeling of statistical hydrodynamics. We also touch 
on decision-making under uncertainty in energy systems. *


The seminars will take place in the _Common area, Old SISSA building, 
second floor - Via Beirut, 2__
_
* You are all most welcome to attend!

Best regards,
Erica

Erica Sarnataro
Group Secretary
Quantitative Life Sciences
The Abdus Salam International Centre for Theoretical Physics (ICTP)
Trieste,  Italy
Tel. +39-040-2240623
www.ictp.it/research/qls.aspx
e-mail:qls at ictp.it