Publications

Marozeau, J. & de Cheveigné, A. (2007). The effect of fundamental frequency on the brightness dimension of timbre. Journal of the Acoustical Society of America, 121(1), 383-387. doi:10.1121/1.2384910

Leman, M., Avanzini, F., de Cheveigné, A. & Bigand, E. (2007). The societal contexts for sound and music computing: Research, education, industry, and socio-culture. Journal of New Music Research, 36(3), 149-167. doi:10.1080/09298210701859164

Le Roux, J., Kameoka, H., Ono, N., de Cheveigné, A. & Sagayama, S. (2007). Single and multiple F-0 contour estimation through parametric spectrogram Modeling of speech in noisy environments. Ieee Transactions on Audio Speech and Language Processing, 15(4), 1135-1145. doi:10.1109/TASL.2007.894510

Sensorimotor Learning of Sound Localization from an Auditory Evoked Behavior

Kuchibhotla, K., Hindmarsh Sten, T., Papadoyannis, E., Elnozahy, S. , Fogelson, K. , Kumar, R., Boubenec, Y., Holland, P., Ostojic, S. & Froemke, R. (2020). Dissociating task acquisition from expression during learning reveals latent knowledge. Nature communications, 10(1), 2151. doi:10.1038/s41467-019-10089-0

David, S., Malaval, N. & Shamma, S. (). Decoupling action potential bias from cortical local field potentials. Computational intelligence and neuroscience. doi:10.1155/2010/393019

Mamassian, P. & Coen-Cagli, R. (2018). An Ideal Observer Model to Probe Human Visual Segmentation of Natural Images. arXiv

Neri, P. (2018). Classification images as descriptive statistics. "Journal of Mathematical Psychology", "82"("1), "26–37"

Wong, D., Di Liberto, G. & de Cheveigné, A. (2019). Accurate Modeling of Brain Responses to Speech. bioRxiv. doi:10.1101/509307

Vacher, J. , Davila, A., Kohn, A. & Coen-Cagli, R. (2020). Texture Interpolation for Probing Visual Perception. Advances in Neural Information Processing Systems (Spotlight – top 5%)

Le Coënt, A., Fribourg, L., Vacher, J. & Wisniewski, R. (2020). Probabilistic reachability and control synthesis for stochastic switched systems using the tamed Euler method. Nonlinear Analysis: Hybrid Systems, 36, 100860Elsevier. doi:10.1016/j.nahs.2020.100860

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

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

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

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.

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

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.

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

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.

Mamassian, P. & Vemuri, B. (1993). ISOPHOTES ON A SMOOTH SURFACE RELATED TO SCENE GEOMETRY. , Vol. 2031: In Geometric Methods in Computer Vision II, 124-133. doi:10.1117/12.146619

Kiselev, I., Ceolini, E., Wong, D., de Cheveigné, A. & Liu, S. (2017). WHISPER: Wirelessly Synchronized Distributed Audio Sensor Platform. In IEEE Workshop on Practical Issues in Building Sensor Network Applications.

Ponsot, E. & Neri, P. (2020). Inter-individual differences in spectrotemporal modulation processing despite similar audiograms : could they be used to assess supra-threshold hearing distortions? In e-Forum Acusticum 2020. doi:10.48465/fa.2020.0808

Mamassian, P., Kersten, D. & Knill, D. (1996). Categorical local-shape perception. Perception, 25(1), 95-107. doi:10.1068/p250095

Mamassian, P. & Kersten, D. (1996). Illumination, shading and the perception of local orientation. Vision Research, 36(15), 2351-2367. doi:10.1016/0042-6989(95)00286-3

Kersten, D., Knill, D., Mamassian, P. & Bülthoff, I. (1996). Illusory motion from shadows. Nature, 379(6560), 31. doi:10.1038/379031a0

Mamassian, P. (1997). Prehension of objects oriented in three-dimensional space. Experimental Brain Research, 114(2), 235-245. doi:10.1007/PL00005632

Knill, D., Mamassian, P. & Kersten, D. (1997). Geometry of shadows. Journal of the Optical Society of America a-Optics Image Science and Vision, 14(12), 3216-3232. doi:10.1364/JOSAA.14.003216

Kersten, D., Mamassian, P. & Knill, D. (1997). Moving cast shadows induce apparent motion in depth. Perception, 26(2), 171-192. doi:10.1068/p260171

Mamassian, P. & Landy, M. (1998). Observer biases in the 3D interpretation of line drawings. Vision Research, 38(18), 2817-2832. doi:10.1016/S0042-6989(97)00438-0