Răzvan Valentin Florian

Publications

• Selected publications
• The chronotron: A neuron that learns to fire temporally precise spike patterns

  R. V. Florian. (2012)

  PLoS ONE, 7(8), e40233.
• Aggregating post-publication peer reviews and ratings

  R. V. Florian. (2012)

  Frontiers in Computational Neuroscience, 6, 31.
• Reinforcement learning through modulation of spike-timing-dependent synaptic plasticity

  R. V. Florian. (2007)

  Neural Computation, 19(6), 1468–1502.
• 2022
• SuperCoder: Program learning under noisy conditions from superposition of states

  A. Davody, M. Safari, & R. V. Florian. (2022)

  Neurocomputing, 489, 323-332.
• 2021
• Mitigating ageing bias in article level metrics using citation network analysis

  I. Tóth, Z. I. Lázár, L. Varga, F. Járai-Szabó, I. Papp, R. V. Florian, & M. Ercsey-Ravasz. (2021)

  Journal of Informetrics, 15(1), 101105.
• 2020
• Training highly effective connectivities within neural networks with randomly initialized, fixed weights

  C. Ivan, & R. V. Florian. (2020)

  arXiv:2006.16627.
• 2018
• Normalizing scientometric indicators of individual publications using local cluster detection methods on citation networks

  L. Varga, D. Deritei, M. Ercsey-Ravasz, R. Florian, Z. I. Lázár, I. Papp, & F. Járai-Szabó. (2018)

  International Journal of Educational and Pedagogical Sciences, 12(9), 1189-1198.
• Learning to generate HTML code from images with no supervisory data

  A. Davody, H. Davoudi, M. S. Baba, & R. V. Florian. (2018)

  In Neural Abstract Machines & Program Induction v2: A Federated Artificial Intelligence Meeting (FAIM) workshop (ICML, IJCAI/ECAI, AAMAS).
• Hierarchical segmentation of graphical interfaces for Document Object Model reconstruction

  C. F. Perțicaș, M. S. Baba, H. Davoudi, & R. V. Florian. (2018)

  In Neural Abstract Machines & Program Induction v2: A Federated Artificial Intelligence Meeting (FAIM) workshop (ICML, IJCAI/ECAI, AAMAS).
• 2017
• Finding patterns in visualizations of programs

  C. F. Perțicaș, B. Indurkhya, R. V. Florian, & L. Csató. (2017)

  In 28th Annual Workshop of the Psychology of Programming Interest Group - PPIG 2017: Proceedings (p. 76-85).
• Hierarchical representations of perceptual and sensorimotor information in deep neural networks

  R. V. Florian. (2017)

  In The Third International Workshop on Intrinsically Motivated Open-ended Learning (IMOL 2017).
• 2016
• Genetic-like algorithm applied on citation networks for evaluating scientific publications

  D. Deritei, L. Varga, I. Papp, F. Járai-Szabó, Z. I. Lázár, R. V. Florian, & M. Ercsey-Ravasz. (2016)

  In Conference on Complex Systems.
• 2015
• A new scale for rating scientific publications

  R. V. Florian. (2015)

  In Proceedings of ISSI 2015: 15th International Society of Scientometrics and Informetrics Conference (p. 419-420)Istanbul, Turkey: Boğaziçi University.
• 2014
• Epistemio Outcomes – a lightweight CRIS for collecting and managing information about scientific publications

  R. V. Florian. (2014)

  In Current Research Information Systems (CRIS 2014).
• Normalized cross-disciplinary article impact evaluation

  L. Varga, F. Járai-Szabó, D. Deritei, Z. I. Lázár, I. Papp, M. Ercsey-Ravasz, & R. V. Florian. (2014)

  In Global TechMining Conference (GTM 2014).
• A new class of metrics for spike trains

  C. V. Rusu, & R. V. Florian. (2014)

  Neural Computation, 26(2), 306–348.
• 2013
• The P-Index: Hirsch index of individual publications

  I. Papp, M. Ercsey-Ravasz, D. Deritei, R. Sumi, F. Járai-Szabó, R. V. Florian, .... (2013)

  In Proceedings of the 14th International Society of Scientometrics and Informetrics Conference (ISSI 2013) (Vol. 2, p. 2086-2088).
• 2012
• Supervised learning in spiking neural networks

  R. V. Florian. (2012)

  In N. M. Seel (Eds.), Encyclopedia of the Sciences of Learning (p. 3245–3247)Boston, MA: Springer US.
• The chronotron: A neuron that learns to fire temporally precise spike patterns

  R. V. Florian. (2012)

  PLoS ONE, 7(8), e40233.
• Aggregating post-publication peer reviews and ratings

  R. V. Florian. (2012)

  Frontiers in Computational Neuroscience, 6, 31.
• Reinforcement learning in spiking neural networks

  R. V. Florian. (2012)

  In N. M. Seel (Eds.), Encyclopedia of the Sciences of Learning (p. 2802–2803)Boston, MA: Springer US.
• 2010
• A new spike train metric

  C. V. Rusu, & R. V. Florian. (2010)

  BMC Neuroscience, 11(Suppl 1), P169.
• Challenges for interactivist-constructivist robotics

  R. V. Florian. (2010)

  New Ideas in Psychology, 28(3), 350–353.
• 2009
• Exploring the link between temporal difference learning and spike-timing-dependent plasticity

  C. V. Rusu, & R. V. Florian. (2009)

  BMC Neuroscience, 10(Suppl 1), P201.
• Temporal difference learning does not always lead to STDP

  R. V. Florian, & C. V. Rusu. (2009)

  In Computational and systems neuroscience 2009 (Vol. 3)Presented at the Computational and systems neuroscience 2009.
• 2008
• Relating reinforcement learning and STDP

  R. V. Florian. (2008)

  In Cosyne Workshop on Spiking Networks and Reinforcement Learning.
• Tempotron-like learning with ReSuMe

  R. V. Florian. (2008)

  In Artificial Neural Networks - ICANN 2008 (Vol. Part II, p. 368-375)Presented at the 18th International Conference on Artificial Neural Networks, Berlin / Heidelberg: Springer.
• 2007
• Irreproducibility of the results of the Shanghai academic ranking of world universities

  R. V. Florian. (2007)

  Scientometrics, 72(1), 25–32.
• Reinforcement learning through modulation of spike-timing-dependent synaptic plasticity

  R. V. Florian. (2007)

  Neural Computation, 19(6), 1468–1502.
• Neuromodulation of STDP and reinforcement learning

  R. V. Florian. (2007)

  In International Workshop on Coherent Behavior in Neuronal Networks (p. 33).
• Challenges for interactivist-constructivist robotics

  R. V. Florian. (2007)

  In Interactivist Summer Institute 2007Paris, France: The American University of Paris.
• 2006
• Phase transition in an optimal clusterization model

  Z. Néda, R. Florian, M. Ravasz, A. Libál, & G. Györgyi. (2006)

  Physica A: Statistical Mechanics and its Applications, 362(2), 357–368.
• Spiking neural controllers for pushing objects around

  R. V. Florian. (2006)

  In From Animals to Animats 9 (p. 570-581)Presented at the 9th International Conference on Simulation of Adaptive Behavior, SAB 2006, Berlin / Heidelberg: Springer.
• Modulation of STDP by a global reward signal leads to reinforcement learning

  R. V. Florian. (2006)

  In Conference on Mathematical Neuroscience (Neuromath06) (p. 45-46).
• Universităţile din România şi clasamentul Shanghai

  R. V. Florian. (2006)

  Revista de politica ştiinţei şi scientometrie, IV(1).
• Reinforcement learning for spiking neural networks with modulated spike-timing-dependent plasticity

  R. V. Florian. (2006)

  In Proceedings of the Tenth International Conference on Cognitive and Neural Systems (p. 126)Boston, MA, USA: Boston University.
• Phase precession and recession with STDP and anti-STDP

  R. V. Florian, & R. C. Mureşan. (2006)

  In Artificial Neural Networks – ICANN 2006 (p. 718-727)Presented at the 16th International Conference on Artificial Neural Networks, Berlin Heidelberg: Springer.
• 2005
• A reinforcement learning algorithm for spiking neural networks

  R. V. Florian. (2005)

  In D. Zaharie, D. Petcu, V. Negru, T. Jebelean, G. Ciobanu, A. Cicortas, et al. (Eds.), Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2005), 25-29 September 2005, Timisoara, Romania (p. 299–306)IEEE Computer Society.
• An evolved spiking neural controller for alternate object pushing by a simulated embodied agent

  R. V. Florian. (2005)

  In Proceedings of the Ninth International Conference on Cognitive and Neural Systems (p. 27)Presented at the Ninth International Conference on Cognitive and Neural Systems, Boston, MA: Boston University.
• Coherence, Memory and Conditioning

  R. C. Mureşan, G. Pipa, R. V. Florian, & D. W. Wheeler. (2005)

  Neural Information Processing - Letters and Reviews, 7(2), 19-28.
• 2004
• Integrating memory, learning, perception and action

  R. V. Florian. (2004)

  In European Research Conference on Neural Mechanisms of Learning and MemoryObernai, France.
• 2003
• Spiking neural networks for the control of simulated embodied artificial intelligent agents

  R. V. Florian. (2003)

  In Annual meeting of Sigma Xi — the Scientific Research SocietyLos Angeles, CA, USA.
• Exploitation of environmentally-derived sensorimotor isomorphisms

  R. V. Florian. (2003)

  In Proceedings of the Seventh International Conference on Cognitive and Neural Systems (p. 50)Boston, MA: Boston University.
• 2002
• Why it is important to build robots capable of doing science

  R. V. Florian. (2002)

  In C. G. Prince, Y. Demiris, Y. Marom, H. Kozima, & C. Balkenius (Eds.), Proceedings of the Second International Workshop on Epigenetic Robotics (Vol. 94, p. 27-34)Lund, Sweden: Lund University.
• 2000
• Optimizing conflicts in the formation of strategic alliances

  R. Florian, & S. Galam. (2000)

  The European Physical Journal B - Condensed Matter and Complex Systems, 16(1), 189-194.
• 1999
• Reconsideration of continuum percolation of isotropically oriented sticks in three dimensions

  Z. Néda, R. Florian, & Y. Brechet. (1999)

  Physical Review E, 59(3), 3717–3719.