Neural Information Processing Scaled for Bioacoustics: NIPS4B

Pr. Stéphane Mallat:

• S. Mallat, Mathematical introduction of scattering operators for translation and rotation invariant representations: Group Invariant Scattering; Communications in Pure and Applied Mathematics, Oct. 2012.
• J. Bruna, S. Mallat, Classification with Scattering Operators, IEEE CVPR 2011
• J. Anden, S. Mallat., Scattering transform applied to audio signals and musical classification: Multiscale Scattering for Audio Classification, ISMIR 2011
• J. Anden and S. Mallat., Modulated source-filter models and their representation in the scattering transform, "Scattering Representation of Modulated Sounds, Proceedings of the DAFx 2012

Pr. Yann LeCun:

• Farabet, C., Couprie, C., Najman, L. and LeCun, Y., Learning Hierarchical Features for Scene Labeling, IEEE Transactions on Pattern Analysis and Machine Intelligence", 2013
• Sermanet, P., Chintala, S. and LeCun, Y., Convolutional Neural Networks Applied to House Numbers Digit Classification, International Conference on Pattern Recognition (ICPR 2012), 2012
• LeCun, Y., Learning Invariant Feature Hierarchies, ECCV 2012, Workshop on Biological and Computer Vision Interfaces, Springer, LNCS, V.7583, Workshop on Biological and Computer Vision Interfaces
• Szlam, A. and Gregor, K. and LeCun, Y., Fast Approximations to Structured Sparse Coding and Applications to Object Classification, ECCV 2012, Springer, LNCS V. 7576
• Alvarez, J. M. and Gevers, T. and LeCun, Y. and Lopez, A. M., Road Scene Segmentation from a Single Image, ECCV 2012, Springer, Lecture Notes in Computer Science, vol. 7578
• Mirowski, P. and LeCun, Y., Statistical Machine Learning and Dissolved Gas Analysis: A Review vol. 27, num. 4, pp. 1791-1799, IEEE Transactions on Power Delivery, October 2012
• Farabet, C. and Couprie, C. and Najman, L. and LeCun, Y., Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers, Proc. International Conference on Machine learning (ICML'12), 2012

Pr. Hervé Glotin:

• S. Paris and al.(2013) Physeter catodon localization by sparse coding, ICML for Bioacoustics workshop, 2013
• Glotin H. (2013), Soundscape Semiotics, Ed. Intech, 220 pp., to appear sept.
• Glotin H., Clark C., LeCun Y., Dugan P., Halkias X. and Sueur J., (2013), Proc. of the first workshop on Machine Learning for Bioacoustics, Vol.1, 104 pages, joint to Int. Conf. on Machine Learning, ICML 2013, Atlanta, ISBN 979-10-90821-02-6
• Halkias X., Paris S., Glotin H. (2013) Classification of Mysticete Sounds using Machine Learning Techniques, Jour. Acoustical Society of America (JASA), to appear oct.
• Chamroukhi F., H. Glotin, (2012) Mixture model-based functional discriminant analysis for curve classification, Int. workshop joint to Conf. on Neural Networks, IJCNN
• Razik J., S Paris, H Glotin (2012) Broadcast News Phoneme Recognition by Sparse Coding, In Patt. Rec. App. & Methods, ICPRAM
• Glotin H. (2011) 'Sparse Complex Scene Analysis - Application to bioacoustics', Project report Institut Universitaire de France
• Pace, F., Benard, F., Glotin, H., Adam, O., and White, P. (2010) Subunit definition for humpback whale call classification, int. journal Applied Acoustics, Elsevier, 11(71)
• Glotin H., Caudal F, Giraudet P. (2008) Whales cocktail party: a real-time tracking of multiple whales, int. Journal Canadian Acoustics, V.36(1), ISSN 0711-6659, ONLINE DEMO here
• Giraudet P. Glotin H. (2006) Real-time 3D tracking of whales by precise and echo-robust TDOAs of clicks extracted from 5 bottom-mounted hydrophones records of the AUTEC, int. journal Applied Acoustics, vol. 67, N 11-12, ONLINE DEMO here
• Benard F., H. Glotin (2010) Automatic indexing and content analysis of whale recordings and XML representation , in Eurasip int. Journal on Advances in Signal Processing
• Benard F., Giraudet P., Glotin H. (2010) 'Whale 3D monitoring using astrophysic NEMO ONDE two meters wide platform with state optimal filtering by Rao-Blackwell Monte Carlo data association', int. jour. App. Acoustics, (71) pp 994-999

Pr. Ofer Tchernichovski:

• Lipkind D, Marcus GF, Bemis DK, Sasahara K, Jacoby N, Takahasi M, Suzuki K, Feher O, Ravbar P, Okanoya K, Tchernichovski O. (2013) Stepwise acquisition of vocal combinatorial capacity in songbirds and human infants. Nature. doi: 10.1038/nature12173
• Ravbar, P., Lipkind, D., Parra, L. C., & Tchernichovski, O. (2012). Vocal Exploration Is Locally Regulated during Song Learning. The Journal of Neuroscience, 7 March 2012, 32(10): 3422-3432
• Lipkind, D., Tchernichovski, O. (2011), Quantification of developmental birdsong learning from the subsyllabic scale to cultural evolution. PNAS. doi: 10.1073/pnas.1012941108
• Kristen K. Maul , Henning U. Voss , Lucas C. Parra, Delanthi Salgado-Commissariat, Douglas Ballon, Ofer Tchernichovski, Santosh A. Helekar (2010), The development of stimulus-specific auditory responses requires song exposure in male but not female zebra finches. Developmental Neurobiology Vol 70-1
• Feher, O., Wang, H., Saar, S., Mitra, PP, Tchernichovski, O. (2009), De novo establishment of wild-type song culture in the zebra finch. Nature 459 2009 DOI: 10.1038
• Saar,S., Mitra, PP (2008), A Technique for Characterizing the Development of Rhythms in Bird Song. PLoS ONE 3(1)
• Tchernichovski, O., Wallman, J. (2008), Neurons of imitation. Nature 451, 17, pp 245-246
• Andrews, P., Saar, S., Wang, H., Valente, D., Serkhane, J., Tchernichovski, O., Golani, I., Mitra, PP. (2006) Multimedia signal processing for behavioral quantification in Neuroscience. ACM Multimedia Conference 2006
• Deregnaucourt S, Mitra PP, Feher O, Pytte C, Tchernichovski O (2005), How sleep affects the developmental learning of bird song. Nature, Vol. 433, No. 7027.

Pr. Thierry Artières:

• Y. Soullard, M. Savinsky, T. Artieres, Joint Semi-Supervised Learning of Hidden Conditional Random Fields and Hidden Markov Models, Journal of Pattern Recognition Letters, accepted, to appear in 2013.
• Y. Ding, T. Artieres, C. Pelachaud, Modeling Multimodal Behaviors From Speech Prosody, International Conference on Intelligent Virtual Agents (IVA), 2013, to appear.
• M. Cisse, T. Artieres; P. Gallinari, Learning compact class codes for fast inference in large multi class classification, European Conference on Machine Learning (ECML), 2012.
• I. Lallemand, D. Schwarz, T. Artieres, A Multiresolution Kernel Distance for SVM Classification of Environmental Sounds, Sound and Music Computing (SMC), 2012.
• M. Radenen, T. Artieres, Contextual Hidden Markov Models, International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012.
• Y. Soullard, T. Artieres, Hybrid HMM and HCRF model for sequence classification, European Symposium on Artificial Neural Networks (ESANN), 2011.

Dr. Xanadu Halkias:

• Halkias X., Paris S., Glotin H., Classification of Mysticete Sounds using Machine Learning Techniques, Journal of the Acoustical Society of America (JASA), to appear Oct. 2013
• Halkias, X. C and Ellis, D., A Comparison of Pitch Extraction Methodologies for Dolphin Vocalizations, Journal of Canadian Acoustics, V 36(1), 2008
• Halkias, X. C and Ellis, D., Call Detection and Extraction Using Bayesian Inference, Applied Acoustics, Special issue on Marine Mammal Detection, vol. 67, no 11-12, Nov-Dec. 2006, pp.1164-1174
• Halkias, X. C and Ellis, D., Estimating the Number of Marine Mammals using Recordings from One Microphone, IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP-06, Toulouse, France, May 2006
• Halkias X., Detection and tracking of dolphin vocalizations, Ph.D, Columbia Unic. 2009
• Martin V., Glotin H., Paris, S., Halkias, X. Prevot, J.-M., Violence Detection in Video by Large Scale Multi-Scale Local Binary Pattern Dynamics, in proc. of MediaEval workshop / ImagEval, 2012.
• Paris, S., Halkias, X., Glotin, H., Sparse Coding of Histograms of Local Binary Patterns Applied for Image Categorization: Towards a Bag-of-Scenes Analysis, ICPR 2012, Japan, Nov.