Publications

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

Millet, J., Caucheteux, C. , Boubenec, Y., Gramfort, A., Dunbar, E., Pallier, C. & King, J. (2022). Toward a realistic model of speech processing in the brain with self-supervised learning. , Vol. 35: In 36th Conference on Neural Information Processing Systems, 33428-33443.

Peperkamp, S., Antoine, V. & Turnbull, R. (2022). Les Liaisons Dangereuses: Quantifying French liaison-induced homophony. In J. Culbertson, A. Perfors, H. Rabagliati & V. Ramenzoni (Eds.), In Proceedings of the 44th Annual Conference of the Cognitive Science Society, 2409-2414.

Peperkamp, S. & Brazeal, J. (2023). Lasting stress ‘deafness’ after auditory training: French listeners revisited. In Proceedings of ICPhS, Prague.

Dailey, M. & Peperkamp, S. (2023). Implicit vs. explicit perception of French optional liaison as a marker of formality. In Proceedings of the 20th International Congress of Phonetic Sciences, Prague, Czech Republic.

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

Aucouturier, J., Liuni, M. & Ponsot, E. (2017). Not so scary anymore : Screaming voices embedded in harmonic contexts are more positive and less arousing. In ESCOM.

Boruta, L., Peperkamp, S., Crabbe, B. & Dupoux, E. (2011 ). Testing the robustness of online word segmentation: effects of linguistic diversity and phonetic variation. In Proceedings of the 2011 Workshop on Cognitive Modeling and Computational Linguistics, ACL, Portland, Oregon, 1-9.

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

Caze, R., Humphries, M. & Gutkin, B. (2012). Spiking and saturating dendrites differentially expand single neuron computation capacity. , Vol. 13: In Twenty First Annual Computational Neuroscience Meeting: CNS*2012, Decatur, GA, USA.

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

Chemla, E. & Spector, B. (2010 ). Experimental Detection of Embedded Implicatures. In Aloni, Maria and Bastiaanse, Harald and de Jager, Tikitu and Schulz, Katrin (Eds.), In Logic, Language and Meaning: 17th Amsterdam Colloquium, Amsterdam, The Netherlands, Springer Berlin Heidelberg, 53–62. doi:10.1007/978-3-642-14287-1_6

Cremers, A. & Chemla, E. (2017). Probability Judgments of Gappy Sentences. In Pistoia-Reda, Salvatore and Filippo Domaneschi (Eds.), Linguistic and Psycholinguistic Approaches on Implicatures and Presuppositions (pp. 111-150).Palgrave

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.

Darcy, I., Peperkamp, S. & Dupoux, E. (2007 ). Bilinguals play by the rules. Perceptual compensation for assimilation in late L2-learners. In Cole, J. and Hualde, J. (Eds.), Laboratory Phonology 9 (pp. 411-442). Berlin: Mouton de Gruyter

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

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

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

Fort, M., Weiss, A., Martin, A. & Peperkamp, S. (2013). Looking for the bouba-kiki effect in prelexical infants. In S. Ouni, F. Berthommier & A. Jesse (Eds.), In Proceedings of the 12th International Conference on Auditory-Visual Speech Processing, INRIA, 71-76.

Geffen, L., Chemla, E. & Steinert-Threlkeld, S. (2020). On the Spontaneous Emergence of Discrete and Compositional Signals. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 4794–4800. doi:10.18653/v1/2020.acl-main.433

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.)

Guevara Rukoz, A., Parlato-Oliveira, E., Yu, S., Hirose, Y., Peperkamp, S. & Dupoux, E. (2017). Predicting epenthetic vowel quality from acoustics. In INTERSPEECH-2017, 596-600.

Guevara-Rukoz, A. , Yu, S. & Peperkamp, S. (2021). Speech perception and loanword adaptations: the case of copy-vowel epenthesis. In Proceedings of INTERSPEECH, Brno, Czech Republic.

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

Havron, N., Babineau, M., Fiévet, A., de Carvalho, A. & Christophe, A. (2019). Young Children Build Syntactic Predictions During Language Processing and Use Them to Learn Novel-Word Meanings. In The 44th Annual Boston University Conference on Language Development, Boston, USA.

Imbert, M. (2020). La fin du regard éclairant. Une révolution dans les sciences de la vision au XIè siècle, Ibn al-Haytham.

Johnson, M., Christophe, A. & Dupoux, E. (2014 ). Modelling function words improves unsupervised word segmentation. In Proceedings of the 52nd Annual meeting of the ACL, 282–292. doi:10.3115/v1/P14-1027

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

Lev-Ari, S., Dodsworth , R., Mielke, J. & Peperkamp, S. (2019). The different roles of expectations in phonetic and lexical processing. In Proceedings of INTERSPEECH, Graz, Austria, ISCA, 2305-2309.