154 citations · 448 across the 31 of their papers we have counts for
8 papers · 1 filter
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…
Learning how to find targets in the micro-world: The case of intermittent active Brownian particles
Michele Caraglio, Harpreet Kaur, Lukas J. Fiderer +4
Finding the best strategy to minimize the time needed to find a given target is a crucial task both in nature and in reaching decisive technological advances. By considering learni…
Quantitative evaluation of methods to analyze motion changes in single-particle experiments
Gorka Muñoz-Gil, Harshith Bachimanchi, Jesús Pineda +33
The analysis of live-cell single-molecule imaging experiments can reveal valuable information about the heterogeneity of transport processes and interactions between cell component…
Quantum circuit synthesis with diffusion models
Florian Fürrutter, Gorka Muñoz-Gil, Hans J. Briegel
Quantum computing has recently emerged as a transformative technology. Yet, its promised advantages rely on efficiently translating quantum operations into viable physical realizat…
Learning minimal representations of stochastic processes with variational autoencoders
Gabriel Fernández-Fernández, Carlo Manzo, Maciej Lewenstein +2
Stochastic processes have found numerous applications in science, as they are broadly used to model a variety of natural phenomena. Due to their intrinsic randomness and uncertaint…
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…