Sampling with flows, diffusion, and autoregressive neural networks from a spin-glass perspective
Recent years witnessed the development of powerful generative models based on flows,
diffusion, or autoregressive neural networks, achieving remarkable success in generating …
diffusion, or autoregressive neural networks, achieving remarkable success in generating …
Satisfiability threshold for random regular NAE-SAT
We consider the random regular k-nae-sat problem with n variables each appearing in
exactly d clauses. For all k exceeding an absolute constant k 0, we establish explicitly the …
exactly d clauses. For all k exceeding an absolute constant k 0, we establish explicitly the …
The backtracking survey propagation algorithm for solving random K-SAT problems
Discrete combinatorial optimization has a central role in many scientific disciplines,
however, for hard problems we lack linear time algorithms that would allow us to solve very …
however, for hard problems we lack linear time algorithms that would allow us to solve very …
Statistical physics of hard optimization problems
L Zdeborová - arXiv preprint arXiv:0806.4112, 2008 - arxiv.org
Optimization is fundamental in many areas of science, from computer science and
information theory to engineering and statistical physics, as well as to biology or social …
information theory to engineering and statistical physics, as well as to biology or social …
On the freezing of variables in random constraint satisfaction problems
G Semerjian - Journal of Statistical Physics, 2008 - Springer
The set of solutions of random constraint satisfaction problems (zero energy groundstates of
mean-field diluted spin glasses) undergoes several structural phase transitions as the …
mean-field diluted spin glasses) undergoes several structural phase transitions as the …
Constraint satisfaction problems with isolated solutions are hard
L Zdeborová, M Mézard - Journal of Statistical Mechanics: Theory …, 2008 - iopscience.iop.org
We study the phase diagram and the algorithmic hardness of the random'locked'constraint
satisfaction problems, and compare them to the commonly studied'non-locked'problems like …
satisfaction problems, and compare them to the commonly studied'non-locked'problems like …
Entropy landscape and non-Gibbs solutions in constraint satisfaction problems
We study the entropy landscape of solutions for the bicoloring problem in random graphs, a
representative difficult constraint satisfaction problem. Our goal is to classify which types of …
representative difficult constraint satisfaction problem. Our goal is to classify which types of …
The threshold for SDP-refutation of random regular NAE-3SAT
Unlike its cousin 3SAT, the NAE-3SAT (not-all-equal-3SAT) problem has the property that
spectral/SDP algorithms can efficiently refute random instances when the constraint density …
spectral/SDP algorithms can efficiently refute random instances when the constraint density …
Biased landscapes for random constraint satisfaction problems
L Budzynski, F Ricci-Tersenghi… - Journal of Statistical …, 2019 - iopscience.iop.org
The typical complexity of constraint satisfaction problems (CSPs) can be investigated by
means of random ensembles of instances. The latter exhibit many threshold phenomena …
means of random ensembles of instances. The latter exhibit many threshold phenomena …
Phase transitions in the q-coloring of random hypergraphs
We study in this paper the structure of solutions in the random hypergraph coloring problem
and the phase transitions they undergo when the density of constraints is varied …
and the phase transitions they undergo when the density of constraints is varied …