Publications

Zeng. H-L, Hertz J., Roudi Y. (2013). L_1 regularization for reconstruction of a non-equilibrium Ising Model, arxiv link

Zeng. H-L, Alava M., Aurell E., Hertz J., Roudi Y. (2013). Maximum likelihood reconstruction for Ising models with asynchronous updates, Phys. Rev. Lett., arxiv link

Latham P., Roudi Y. (2013). Role of stimulus-dependent correlation in population coding,”Principle of Neural Coding”, S. Panzeri and R. Q. Quiroga Eds, arxiv link

Hertz J., Roudi Y., Tyrcha J. (2013) Ising Models for Inferring Network Structure From Spike Data, “Principles of Neural Coding, S. Panzeri and R. Q. Quiroga Eds, arxiv link

Tyrcha J., Roudi Y., Marsili M., Hertz J. (2013). Effect of Nonstationarity on Models Inferred from Neural Data, J. Stat. Mech., P03005

Dunn B., Roudi Y. (2013). Learning and inference in a non-equilibrium Ising model with hidden nodes. Phys. Rev. E, 87: 022127

Couey J. J.*, Witoelar A.*, Zhang Sh-J.*, Ye J., Dunn B., Czajkowski R., Moser M-B., Moser E.I.,Roudi Y., Witter M.P. (2013). Entorhinal layer II recurrent inhibitory network is sufficient to generate grid cell firing patterns, Nat. Neuro., 16(3):309, *equal contribution

Bonnevie T., Dunn B., Fyhn M., Hafting T., Derdikman D., Kubie J.L., Roudi Y., Moser E.I., Moser M-B. (2013). Entorhinal grid cells require excitatory drive from the hippocampus, Nat. Neuro., 16(3):318

Bomash I., Roudi Y., Nirenberg S. (2013). A virtual retina: a tool for studying population coding, PLoS One, 8(1): e53363

Sakallariu J., Roudi Y., Hertz J., Mezard M. (2012). Effect of coupling asymmetry on mean-field solutions of direct and inverse Sherrington-Kirkpatrick model. Phil. Mag., 92: 272

Roudi Y., Hertz J. (2011). Dynamical TAP equations for non-equilibrium Ising spin glasses, J. Stat. Mech., P03031

Roudi Y., Hertz J. (2011). Mean field theory for non-equilibrium network reconstruct, Phys. Rev. Lett., 106, 048702

Hertz J., Roudi Y., Thorning A., Tyrcha J., Aurell E., Zeng H. (2010). Inferring network connectivity using kinetic Ising models. BMC Neuroscience 2010, 11 (Suppl 1):P51

Aurell E., Ollion C., Roudi Y. (2010). Dynamics and performance of Susceptibility Propagation on synthetic data. EPJ B. 77:587

Roudi Y., Aurell E., Hertz J. (2009). Statistical physics of pairwise probability models. Front. in Comp. Neurosci., 3:22

Roudi Y., Tyrcha J., Hertz J. (2009). Fast and reliable methods for extracting functional connectivity in large populations. BMC Neuroscience, 10, Suppl. 1

Roudi Y., Tyrcha J., Hertz J. (2009). Ising Model for Neural Data: Model Quality and Approximate Methods for Extracting Functional Connectivity. Phys. Rev. E, 79, 051915

Latham P. E., Roudi Y. (2009). Mutual Information. Scholarpedia, 4(1):1658.

Roudi Y., Nirenberg S., Latham P. E. (2009). Pairwise maximum entropy models for studying large biological systems: when they can and when they can’t work. PLoS Comp. Biol., 5(5): e1000380.

Roudi Y., Treves A. (2008). Representing where along with what information in a model of a cortical patch. PLoS Comp. Biol. 4(3): e1000012.

Roudi Y., Latham P. E. (2007). A balanced memory network, PLoS Comp. Biol. 3:e141.

Roudi Y., Treves A. (2006). Localized activity profiles and storage capacity of rate-based autoassociative networks. Phys. Rev. E, 73, 061904.

Roudi Y., Treves A. (2006). An evolutionary niche for quantitative theoretical analyses?, Behavioral and Brain Sciences. 29:23.

Treves A., Roudi Y. (2005). On the evolution of the brain. In Methods and models in neurophysics, Chow CC et al Eds, Les Houches summer school session 80 (Elsevier).

Roudi Y., Treves A. (2004).An associative network with spatially organized connectivity. J. Stat. Mech.:Theory and Exp. P07010.

Roudi Y., Treves A., (2003). Disappearance of spurious states in analog associative memories. Phys. Rev. E 67, 041906.

Roudi Y., (1999). Breaking the strings that connect hanging masses. Journal of Physics (Iran), 17:99.