154 citations · 448 across the 31 of their papers we have counts for
12 papers · 1 filter
Emergent aggregation from collective foraging
Gorka Muñoz-Gil, Andrea López-Incera, Vide Ramsten +3
Collective behaviour in living systems is usually modelled as the outcome of a \emph{direct} social drive: agents are rewarded, or hard-wired, to align with or approach their neigh…
Learning to reset in target search problems
Gorka Muñoz-Gil, Hans J. Briegel, Michele Caraglio
Target search problems are central to a wide range of fields, from biological foraging to the optimization algorithms. Recently, the ability to reset the search has been shown to s…
Universal representation by Boltzmann machines with Regularised Axons
Przemysław R. Grzybowski, Antoni Jankiewicz, Eloy Piñol +7
It is widely known that Boltzmann machines are capable of representing arbitrary probability distributions over the values of their visible neurons, given enough hidden ones. Howev…
Optimal foraging strategies can be learned
Gorka Muñoz-Gil, Andrea López-Incera, Lukas J. Fiderer +1
The foraging behavior of animals is a paradigm of target search in nature. Understanding which foraging strategies are optimal and how animals learn them are central challenges in…
Preface: Characterisation of Physical Processes from Anomalous Diffusion Data
Carlo Manzo, Gorka Muñoz-Gil, Giovanni Volpe +3
Preface to the special issue "Characterisation of Physical Processes from Anomalous Diffusion Data" associated with the Anomalous Diffusion Challenge ( https://andi-challenge.org )…
Unsupervised learning of anomalous diffusion data
Gorka Muñoz-Gil, Guillem Guigó i Corominas, Maciej Lewenstein
The characterization of diffusion processes is a keystone in our understanding of a variety of physical phenomena. Many of these deviate from Brownian motion, giving rise to anomal…
AnDi: The Anomalous Diffusion Challenge
Gorka Muñoz-Gil, Giovanni Volpe, Miguel Angel Garcia-March +3
The deviation from pure Brownian motion generally referred to as anomalous diffusion has received large attention in the scientific literature to describe many physical scenarios.…
Efficient training of energy-based models via spin-glass control
Alejandro Pozas-Kerstjens, Gorka Muñoz-Gil, Eloy Piñol +4
We introduce a new family of energy-based probabilistic graphical models for efficient unsupervised learning. Its definition is motivated by the control of the spin-glass propertie…
Machine learning method for single trajectory characterization
Gorka Muñoz-Gil, Miguel Angel Garcia-March, Carlo Manzo +2
In order to study transport in complex environments, it is extremely important to determine the physical mechanism underlying diffusion, and precisely characterize its nature and p…
Diffusion through a network of compartments separated by partially-transmitting boundaries
Gorka Muñoz-Gil, Miguel Angel García-March, Carlo Manzo +2
We study the random walk of a particle in a compartmentalized environment, as realized in biological samples or solid state compounds. Each compartment is characterized by its leng…
Transient subdiffusion from an Ising environment
G. Muñoz-Gil, C. Charalambous, M. A. García-March +4
We introduce a model, in which a particle performs a continuous time random walk (CTRW) coupled to an environment with Ising dynamics. The particle shows locally varying diffusivit…
Nonergodic subdiffusion from transient interactions with heterogeneous partners
C. Charalambous, G. Muñoz-Gil, A. Celi +4
Spatiotemporal disorder has been recently associated to the occurrence of anomalous nonergodic diffusion of molecular components in biological systems, but the underlying microscop…