Publications

Caze, R., Humphries, M., Gutkin, B. & Schultz, S. (2013). A difficult classification for neurons without dendrites. In Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on, San Diego, CA, USA, IEEE, 215-218. doi:10.1109/NER.2013.6695910

Wang, X., Du, J., Cristia, A., Sun, L. & Lee, C. (2020). A Study of Child Speech Extraction Using Joint Speech Enhancement and Separation in Realistic Conditions. In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, 7304-7308. doi:10.1109/ICASSP40776.2020.9053875

Pressnitzer, D., Agus, T., Kang, H. , Graves, J. & Andrillon, T. (2021). Apprentissage de motifs sonores. In S. Samson, B. Tillmann, C. Jourdan, V. Brun (Eds.), Audition et Cognition Montpellier: Sauramps Medical

Mamassian, P., Landy, M., Maloney, L., Rao, R., Olshausen, B. & Lewicki, M. (2002). Bayesian modelling of visual perception. In R. Rao, B. Olshausen & M. Lewicki (Eds.), Probabilistic Models of the Brain: Perception and Neural Function (pp. 13-36). Cambridge, MA: MIT Press

Zakharov, D., Dogonasheva, O. & Gutkin, B. (2021). Bistability of globally synchronous and chimera states in a ring of phase oscillators coupled by a cosine kernel. In 2021 5th Scientific School Dynamics of Complex Networks and their Applications (DCNA), 211-214. doi:10.1109/DCNA53427.2021.9586968

Dogonasheva, O., Gutkin, B. & Zakharov, D. (2021). Calculation of travelling chimera speeds for dynamical systems with ring topologies. In 5th Scientific School Dynamics of Complex Networks and their Applications (DCNA), 61-64. doi:10.1109/DCNA53427.2021.9586903

Radushev, D. , Dogonasheva, O., Gutkin, B. & Zakharov, D. (2023). Chimera states in a ring of non-locally connected interneurons. In 7th Scientific School Dynamics of Complex Networks and their Applications (DCNA), Kaliningrad, Russian Federation, 229-232. doi:10.1109/DCNA59899.2023.10290318

Osses , A. & Varnet, L. (2021). Consonant-in-noise discrimination using an auditory model with different speech- based decision devices. In DAGA, Vienna Austria.

Caze, R., Humphries, M. & Gutkin, B. (2013). Dendrites enhance both single neuron and network computation. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Caucheteux, C. , Gramfort, A. & King, J. (2021). Disentangling syntax and semantics in the brain with deep networks. , Vol. 139: In International Conference on Machine Learning, PMLR, 1336-1348.

Dubreuil, A., Valente, A., Mastrogiuseppe, F. & Ostojic, S. (2019). Disentangling the roles of dimensionality and cell classes in neural computation. In NeurIPS Workshop.

Kuznetsov, A. & Gutkin, B. (2015). Dopaminergic cell Models. The Encyclopedia of Computational Neuroscience (pp. 2958-2965).

Dumont, G., Maex, R. & Gutkin, B. (2018). Dopaminergic Neurons in the Ventral Tegmental Area and Their Dysregulation in Nicotine Addiction. In Alan Anticevic and John D. Murray (Eds.), Computational Psychiatry: Mathematical Modeling of Mental Illness (pp. 47-84). doi:10.1016/B978-0-12-809825-7.00003-1

Graupner, M. & Gutkin, B. (2012). Dynamical Approaches to understanding cholinergic control of nicotine action pathways in the dopaminergic reward circuits. Computational Neuroscience of Drug Addiction (Springer ed.).Ahmed and Gutkin (eds.)

Cristia, A. & Peperkamp, S. (2012). Generalizing without encoding specifics: Infants infer phonotactic patterns on sound classes. In Proceedings of the 36th Annual Boston University Conference on Language Development, 126-138.

Futaisi Al, N., Cristia, A. & Schuller, B. (2023). Hearttoheart: The Arts of Infant Versus Adult-Directed Speech Classification. In ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 1-5. doi:10.1109/ICASSP49357.2023.10096728

Berthommier, F. & Lorenzi, C. (2021). Implications of Physiological Mechanisms of Amplitude Modulation Processing for Modeling Complex Sounds Analysis and Separation. (pp. 12). doi:10.1201/9781003064183

Loukatou, G., Le Normand, M. & Cristia, A. (2019). Is it easier to segment words from infant-directed speech? Modeling evidence from an ecological French corpus. In Proceedings of the 41st Conference of Cognitive Science Society..

Loukatou, G., Moran, S., Blasi, D., Stoll, S. & Cristia, A. (2019). Is word segmentation child’s play in all languages? In Proceedings of the Association for Computational Linguistics.

Lussange, J., Belianin, A., Bourgeois-Gironde, S. & Gutkin, B. (2021). Learning and Cognition in Financial Markets: A Paradigm Shift for Agent-Based Models. Advances in Intelligent Systems and Computing (Vol. 1252, pp. 241-255). doi:10.1007/978-3-030-55190-2_19

Zuk, N. , Di Liberto, G. & Lalor, E. (2019). Linear-nonlinear Bernoulli modeling for quantifying temporal coding of phonemes in brain responses to continuous speech. In 2019 Conference on Cognitive Computational Neuroscience, Berlin, Germany.

Remme, M., Lengyel, M. & Gutkin, B. (2014). Phase Response Methods in Dendritic Dynamics. In Schultheiss et al (eds) (Eds.), Phase Response Cruves in NeuroscienceSpringer

Erdmann, A. , Joseph Wrisley, D., Allen, B. , Brown, C. , Cohen-Bodenes, S., Elsner, M. , Feng, Y. , D Joseph, B. , Joyeux-Prunel, B. & de Marneffe, M. (2019). Practical, Efficient, and Customizable Active Learning for Named Entity Recognition in the Digital Humanities. In Proceedings of the 2019 Conference of the North, 2223-2234. doi:10.18653/v1/N19-1231

Zakharov, D., Dogonasheva, O. & Gutkin, B. (2020). Role of Pyramidal Cell M-current in Weak Pyramidal/Interneuronal Gamma Cluster Formation. In 2020 4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR), Innopolis, Russia, IEEE. doi:10.1109/DCNAIR50402.2020.9216942

Ryant, N., Church, K., Cieri, C., Cristia, A., Ganapathy, S. & Liberman, M. (2019). Second DIHARD Diarization Challenge: Dataset, task, and baselines. In Proceedings of Interspeech, Graz, Austria.

Thoret, E., Andrillon, T., Gauriau, C., Léger, D. & Pressnitzer, D. (2020). Sleep deprivation impacts speech spectro-temporal modulations. In e-FA2020 (e- Forum Acusticum 2020 ), Lyon, France.

Shamma, S. (2020). Temporal Coherence Principle in Scene Analysis. The Senses: A Comprehensive Reference (Second Edition) (Vol. 2, pp. 777-790).Elsevier. doi:10.1016/B978-0-12-809324-5.24252-1

Schuller, B., Batliner, A., Bergler, C., Pokorny, F., Krajewski, J., Cychosz, M., Vollmann, R., Roelen, S., Schnieder, S., Bergelson, E. & Cristia, A. (2019). The INTERSPEECH 2019 Computational Paralinguistics Challenge: Styrian Dialects, Continuous Sleepiness, Baby Sounds & Orca Activity. In Proceedings of Interspeech, Graz, Austria.

Semenzin, C. , Hamrick, L., Seidl, A., Kelleher, B. & Cristia, A. (2021). Theory evaluation in the age of cumulative science. In 2021 IEEE Spoken Language Technology Workshop (SLT), Shenzhen, China, 1079-1085. doi:10.1109/SLT48900.2021.9383511

Gutkin, B. (2015). Theta-neurons. In Springer Verlag (Eds.), Encyclopedia of Comptutational Neuroscience (pp. 1034-1042).