Rodrigo Echeveste
Rodrigo Echeveste
Research Institute for Signals, Systems and Computational Intelligence sinc(i) (FICH-UNL/CONICET
Verified email at - Homepage
Cited by
Cited by
Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference
R Echeveste, L Aitchison, G Hennequin, M Lengyel
Nature Neuroscience 23 (9), 1138–1149, 2020
Generating functionals for computational intelligence: The Fisher information as an objective function for self-limiting Hebbian learning rules
R Echeveste, C Gros
Frontiers in Robotics and AI 1, 1, 2014
Percepción sensorial en niños autistas.
RS Echeveste, I Samengo (Supervisor)
Universidad Nacional de Cuyo, 2011
Two-trace model for spike-timing-dependent synaptic plasticity
R Echeveste, C Gros
Neural Computation 27 (3), 672-698, 2015
Energetic substrate availability regulates synchronous activity in an excitatory neural network
DS Tourigny, MKA Karim, R Echeveste, MRN Kotter, JS O’Neill
PloS one 14 (8), e0220937, 2019
EI balance emerges naturally from continuous Hebbian learning in autonomous neural networks
P Trapp, R Echeveste, C Gros
Scientific reports 8 (1), 1-12, 2018
The Fisher Information as a Neural Guiding Principle for Independent Component Analysis
R Echeveste, S Eckmann, C Gros
Entropy 17 (6), 3838-3856, 2015
Domain Generalization via Gradient Surgery
L Mansilla, R Echeveste, DH Milone, E Ferrante
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
The subjective metric of remembered colors: A Fisher-information analysis of the geometry of human chromatic memory
M da Fonseca, N Vattuone, F Clavero, R Echeveste, I Samengo
PloS one 14 (1), e0207992, 2019
The Redemption of Noise: Inference with Neural Populations
R Echeveste, M Lengyel
Trends in Neurosciences 41 (11), 767-770, 2018
Drifting States and Synchronization Induced Chaos in Autonomous Networks of Excitable Neurons
R Echeveste, C Gros
Frontiers in Computational Neuroscience 10, 98, 2016
An objective function for self-limiting neural plasticity rules.
R Echeveste, C Gros
European Symposium on Artificial Neural Networks, Computational …, 2015
Asymptotic scaling properties of the posterior mean and variance in the Gaussian scale mixture model
R Echeveste, G Hennequin, M Lengyel
arXiv preprint arXiv:1706.00925, 2017
Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference
R Echeveste, E Ferrante, DH Milone, I Samengo
Network Neuroscience, 1-27, 2021
Desbalance de datos en términos de atributos protegidos: análisis de su impacto en un clasificador lineal
E Escalas, R Echeveste, V Peterson, E Ferrante
XXI Simposio Argentino de Inteligencia Artificial (ASAI 2020)-JAIIO 49 …, 2020
Hebbian learning deduced from the stationarity principle leads to balanced chaos in fully adapting autonomously active networks
C Gros, P Trapp, R Echeveste
Lecture Notes in Computer Science (including subseries Lecture Notes in …, 2017
Information-theoretical foundations of hebbian learning
C Gros, R Echeveste
Lecture Notes in Computer Science (including subseries Lecture Notes in …, 2016
An objective function for Hebbian self-limiting synaptic plasticity rules
C Gros, S Eckmann, R Echeveste
APS March Meeting Abstracts 2016, E41. 001, 2016
Synchronization in a non-uniform network of excitatory spiking neurons
R Echeveste, C Gros
APS March Meeting Abstracts 2016, E41. 004, 2016
Complementary approaches to synaptic plasticity: from objective functions to Biophysics
R Echeveste
Goethe Universität Frankfurt, 2016
The system can't perform the operation now. Try again later.
Articles 1–20