Zobrazeno 1 - 10
of 496
pro vyhledávání: '"Biroli, Giulio"'
Publikováno v:
Comptes Rendus. Physique, Vol , Iss , Pp 1-15 (2023)
The Random First Order Transition (RFOT) theory started with the pioneering work of Kirkpatrick, Thirumalai and Wolynes. It leverages methods and advances of the theory of disordered systems. It fares remarkably well at reproducing the salient experi
Externí odkaz:
https://doaj.org/article/ad9c895f8bea4803bd3f65b887213ac0
Disordered systems generically exhibit aging and a glass transition. Previous studies have long suggested that non-reciprocity tends to destroy glassiness. Here, we show that this is not always the case using a bipartite spherical Sherrington-Kirpatr
Externí odkaz:
http://arxiv.org/abs/2408.17360
Autor:
Biroli, Giulio, Mézard, Marc
This paper studies Kernel Density Estimation for a high-dimensional distribution $\rho(x)$. Traditional approaches have focused on the limit of large number of data points $n$ and fixed dimension $d$. We analyze instead the regime where both the numb
Externí odkaz:
http://arxiv.org/abs/2408.05807
Isolated quantum many-body systems which thermalize under their own dynamics are expected to act as their own thermal baths, thereby bringing their local subsystems to thermal equilibrium. Here we show that the infinite-dimensional limit of a quantum
Externí odkaz:
http://arxiv.org/abs/2405.19884
In this paper, we investigate the feature encoding process in a prototypical energy-based generative model, the Restricted Boltzmann Machine (RBM). We start with an analytical investigation using simplified architectures and data structures, and end
Externí odkaz:
http://arxiv.org/abs/2405.14689
Publikováno v:
Mach. Learn.: Sci. Technol. 5, 035053 (2024)
Normalizing flows can transform a simple prior probability distribution into a more complex target distribution. Here, we evaluate the ability and efficiency of generative machine learning methods to sample the Boltzmann distribution of an atomistic
Externí odkaz:
http://arxiv.org/abs/2404.09914
We provide an analytical study of the evolution of the Hessian during gradient descent dynamics, and relate a transition in its spectral properties to the ability of finding good minima. We focus on the phase retrieval problem as a case study for com
Externí odkaz:
http://arxiv.org/abs/2403.02418
Using statistical physics methods, we study generative diffusion models in the regime where the dimension of space and the number of data are large, and the score function has been trained optimally. Our analysis reveals three distinct dynamical regi
Externí odkaz:
http://arxiv.org/abs/2402.18491
Autor:
Chacko, Rahul N., Landes, François P., Biroli, Giulio, Dauchot, Olivier, Liu, Andrea J., Reichman, David R.
Publikováno v:
Physical Review X 14.3 (2024): 031012
Convincing evidence of domain growth in the heating of ultrastable glasses suggests that the equilibration dynamics of super-cooled liquids could be driven by a nucleation and growth mechanism. We investigate this possibility by simulating the equili
Externí odkaz:
http://arxiv.org/abs/2312.15069
A central theoretical issue at the core of the current research on many-body localization (MBL) consists in characterizing the statistics of rare long-range resonances in many-body eigenstates. This is of paramount importance to understand: (i) the c
Externí odkaz:
http://arxiv.org/abs/2312.14873