Zero-Lag Long Range Synchronization of Neurons Is Enhanced by Dynamical Relaying. - Raul Vicente; Gordon Pipa; Ingo Fischer; Claudio R. Mirasso (ICANN (1), 2007)

Auto-structure of Presynaptic Activity Defines Postsynaptic Firing Statistics and Can Modulate STDP-Based Structure Formation and Learning. - Gordon Pipa; Raul Vicente; Alexander Tikhonov (ICANN (2), 2008)

Contour Integration and Synchronization in Neuronal Networks of the Visual Cortex. - Ekkehard Ullner; Raul Vicente; Gordon Pipa; Jordi García-Ojalvo (ICANN (2), 2008)

A Linear Model of Phase-Dependent Power Correlations in Neuronal Oscillations. - David Eriksson; Raul Vicente; Kerstin Erika Schmidt (Frontiers Comput. Neurosci., 2011)

Spike Train Auto-Structure Impacts Post-Synaptic Firing and Timing-Based Plasticity. - Bertram Scheller; Marta Castellano; Raul Vicente; Gordon Pipa (Frontiers Comput. Neurosci., 2011)

Transfer entropy - a model-free measure of effective connectivity for the neurosciences. - Raul Vicente; Michael Wibral; Michael Lindner; Gordon Pipa (J. Comput. Neurosci., 2011)

Revisiting Wiener's principle of causality - interaction-delay reconstruction using transfer entropy and multivariate analysis on delay-weighted graphs. - Michael Wibral; Patricia Wollstadt; Ulrich Meyer 001; Nicolae Pampu; Viola Priesemann; Raul Vicente (EMBC, 2012)

Emergent bimodal firing patterns implement different encoding strategies during gamma-band oscillations. - Belén Sancristóbal; Raul Vicente; José M. Sancho; Jordi García-Ojalvo (Frontiers Comput. Neurosci., 2013)

Efficient transfer entropy analysis of non-stationary neural time series. - Patricia Wollstadt; Mario Martínez-Zarzuela; Raul Vicente; Francisco Javier Díaz Pernas; Michael Wibral (CoRR, 2014)

Role of frequency mismatch in neuronal communication through coherence. - Belén Sancristóbal; Raul Vicente; Jordi García-Ojalvo (J. Comput. Neurosci., 2014)

Multiagent Cooperation and Competition with Deep Reinforcement Learning. - Ardi Tampuu; Tambet Matiisen; Dorian Kodelja; Ilya Kuzovkin; Kristjan Korjus; Juhan Aru; Jaan Aru; Raul Vicente (CoRR, 2015)

Assessing Coupling Dynamics from an Ensemble of Time Series. - Germán Gómez-Herrero; Wei Wu 003; Kalle Rutanen; Miguel C. Soriano; Gordon Pipa; Raul Vicente (Entropy, 2015)

Bivariate Partial Information Decomposition: The Optimization Perspective. - Abdullah Makkeh; Dirk Oliver Theis; Raul Vicente (Entropy, 2017)

Analyzing Information Distribution in Complex Systems. - Sten Sootla; Dirk Oliver Theis; Raul Vicente (Entropy, 2017)

Machine Learning for detection of viral sequences in human metagenomic datasets. - Zurab Bzhalava; Ardi Tampuu; Piotr Bala; Raul Vicente; Joakim Dillner (BMC Bioinform., 2018)

What deep learning can tell us about higher cognitive functions like mindreading? - Jaan Aru; Raul Vicente (CoRR, 2018)

Do deep reinforcement learning agents model intentions? - Tambet Matiisen; Aqeel Labash; Daniel Majoral; Jaan Aru; Raul Vicente (CoRR, 2018)

APES: a Python toolbox for simulating reinforcement learning environments. - Aqeel Labash; Ardi Tampuu; Tambet Matiisen; Jaan Aru; Raul Vicente (CoRR, 2018)

BROJA-2PID: A Robust Estimator for Bivariate Partial Information Decomposition. - Abdullah Makkeh; Dirk Oliver Theis; Raul Vicente (Entropy, 2018)

Direct information transfer rate optimisation for SSVEP-based BCI. - Anti Ingel; Ilya Kuzovkin; Raul Vicente (CoRR, 2019)

The many faces of deep learning. - Raul Vicente (CoRR, 2019)

MAXENT3D_PID: An Estimator for the Maximum-Entropy Trivariate Partial Information Decomposition. - Abdullah Makkeh; Daniel Chicharro; Dirk Oliver Theis; Raul Vicente (Entropy, 2019)

IDTxl: The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks. - Patricia Wollstadt; Joseph T. Lizier; Raul Vicente; Conor Finn; Mario Martínez-Zarzuela; Pedro A. M. Mediano; Leonardo Novelli; Michael Wibral (J. Open Source Softw., 2019)

Efficient neural decoding of self-location with a deep recurrent network. - Ardi Tampuu; Tambet Matiisen; H. Freyja Ólafsdóttir; Caswell Barry; Raul Vicente (PLoS Comput. Biol., 2019)

Disentangling causal effects for hierarchical reinforcement learning. - Oriol Corcoll; Raul Vicente (CoRR, 2020)

Partial Information Decomposition of Boolean Functions: a Fourier Analysis perspective. - Abdullah Makkeh; Dirk Oliver Theis; Raul Vicente (CoRR, 2020)

Deep Learning with a Single Neuron: Folding a Deep Neural Network in Time using Feedback-Modulated Delay Loops. - Florian Stelzer; André Röhm; Raul Vicente; Ingo Fischer; Serhiy Yanchuk (CoRR, 2020)

Perspective Taking in Deep Reinforcement Learning Agents. - Aqeel Labash; Jaan Aru; Tambet Matiisen; Ardi Tampuu; Raul Vicente (Frontiers Comput. Neurosci., 2020)

A model for time interval learning in the Purkinje cell. - Daniel Majoral; Ajmal Zemmar; Raul Vicente (PLoS Comput. Biol., 2020)

Did I do that? Blame as a means to identify controlled effects in reinforcement learning. - Oriol Corcoll; Raul Vicente (CoRR, 2021)

Modelling the Impact of Robotics on Infectious Spread Among Healthcare Workers. - Raul Vicente; Youssef Mohamed; Víctor M. Eguíluz; Emal Zemmar; Patrick Bayer; Joseph S. Neimat; Juha Hernesniemi; Bradley J. Nelson; Ajmal Zemmar (Frontiers Robotics AI, 2021)

Disentangling Controlled Effects for Hierarchical Reinforcement Learning. - Oriol Corcoll; Raul Vicente (CLeaR, 2022)

Quantifying Reinforcement-Learning Agent's Autonomy, Reliance on Memory and Internalisation of the Environment. - Anti Ingel; Abdullah Makkeh; Oriol Corcoll; Raul Vicente (Entropy, 2022)

Did I do that? Blame as a means to identify controlled effects in reinforcement learning. - Oriol Corcoll; Youssef Sherif Mansour Mohamed; Raul Vicente (Trans. Mach. Learn. Res., 2022)

Emergence of Adaptive Circadian Rhythms in Deep Reinforcement Learning. - Aqeel Labash; Florian Stelzer; Daniel Majoral; Raul Vicente Zafra (ICML, 2023)

Emergence of Adaptive Circadian Rhythms in Deep Reinforcement Learning. - Aqeel Labash; Florian Fletzer; Daniel Majoral; Raul Vicente (CoRR, 2023)

Mind the gap: challenges of deep learning approaches to Theory of Mind. - Jaan Aru; Aqeel Labash; Oriol Corcoll; Raul Vicente (Artif. Intell. Rev., 2023)

Exploring Commonalities in Explanation Frameworks: A Multi-Domain Survey Analysis. - Eduard Barbu; Marharyta Domnich; Raul Vicente; Nikos Sakkas (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2024)

Enhancing Counterfactual Explanation Search with Diffusion Distance and Directional Coherence. - Marharyta Domnich; Raul Vicente (xAI (3), 2024)

COIN: Counterfactual Inpainting for Weakly Supervised Semantic Segmentation for Medical Images. - Dmytro Shvetsov; Joonas Ariva; Marharyta Domnich; Raul Vicente; Dmytro Fishman (xAI (3), 2024)

Exploring Commonalities in Explanation Frameworks: A Multi-Domain Survey Analysis. - Eduard Barbu; Marharyta Domnich; Raul Vicente; Nikos Sakkas; André Morim (CoRR, 2024)

Towards Unifying Evaluation of Counterfactual Explanations: Leveraging Large Language Models for Human-Centric Assessments. - Marharyta Domnich; Julius Välja; Rasmus Moorits Veski; Giacomo Magnifico; Kadi Tulver; Eduard Barbu; Raul Vicente (AAAI, 2025)

Predicting Satisfaction of Counterfactual Explanations from Human Ratings of Explanatory Qualities. - Marharyta Domnich; Rasmus Moorits Veski; Julius Välja; Kadi Tulver; Raul Vicente (CoRR, 2025)