Official repository of "Spontaneous symmetry breaking in generative diffusion models"

A program implementing Metropolis Monte Carlo for the 2D square-lattice Ising model and the spin block renormalization

PyGL: statistical field theory in Python. github.com/rajeshrinet/pygl

lindemann is a python package to calculate the Lindemann index of a lammps trajectory

Unsupervised learning for discovering phase transition for various spin models.

Monte Carlo simulation of 2D Ising Model. Final project of the LoCP-A course during 2020/2021 at Unipd

Machine learning and the Ising model phase transition.

various codes related to compressed sensing that have been used in my publications

Which dynamical regime is beneficial for biological systems in the context of the criticality hypothesis? Agent-based evolutionary foraging game with experiments to evaluate generalizability, ability to perform complex tasks and evolvability of agents with respect to their dynamical regime. Paper: https://arxiv.org/abs/2103.12184

Rapid detection of phase transitions from Monte Carlo samples before equilibrium

Machine Learning Phase Transitions

FiniteSizeScaling.jl: A Julia data analysis package for finding optimized values of phase transition parameters and critical exponents.

💻 Phase Transition for Random Graphs (A-FIB)

Binary 2D alloy phase transition simulation with Monte Carlo method and Ising model

Another phase transition in the Axelrod model

Implementation of the one dimensional Contact Process (SIS model) and two dimensional SIR model in order to find critical exponents of Percolation

Probing hidden spin order with interpretable machine learning (mirrored from GitLab)

Paper: https://doi.org/10.1162/isal_a_00412 Which dynamical regime is beneficial for biological systems? Agent-based evolutionary foraging game with experiments to evaluate generalizability, ability to perform complex tasks and evolvability.

Probabilistic PCA for missing data: learning curves shows a phase transition and missing rate acts as an effective reduction in the signal-to-noise ratio, not the sample size.

Multi-condensate state as a functional strategy to optimize the cell signaling output