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Yann LeCun

Silver Professor; Professor of Computer Science

    1985 …2019

    Research output per year

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    Research Output

    2019

    1.1 Deep Learning Hardware: Past, Present, and Future

    Lecun, Y., Mar 6 2019, 2019 IEEE International Solid-State Circuits Conference, ISSCC 2019. Institute of Electrical and Electronics Engineers Inc., p. 12-19 8 p. 8662396. (Digest of Technical Papers - IEEE International Solid-State Circuits Conference; vol. 2019-February).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    A hierarchical loss and its problems when classifying non-hierarchically

    Wu, C., Tygert, M. & LeCun, Y., 2019, In : PloS one. 14, 12, e0226222.

    Research output: Contribution to journalArticle

    Open Access

    Comparing dynamics: deep neural networks versus glassy systems

    Baity-Jesi, M., Sagun, L., Geiger, M., Spigler, S., Ben Arous, G., Cammarota, C., Lecun, Y., Wyart, M. & Biroli, G., Dec 20 2019, In : Journal of Statistical Mechanics: Theory and Experiment. 2019, 12, 124013.

    Research output: Contribution to journalArticle

    DesIGN: Design inspiration from generative networks

    Sbai, O., Elhoseiny, M., Bordes, A., LeCun, Y. & Couprie, C., 2019, Computer Vision – ECCV 2018 Workshops, Proceedings. Leal-Taixé, L. & Roth, S. (eds.). Springer Verlag, p. 37-44 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11131 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Energy-based generative adversarial networks

    Zhao, J., Mathieu, M. & LeCun, Y., Jan 1 2019.

    Research output: Contribution to conferencePaper

    Energy-based generative adversarial networks

    Zhao, J., Mathieu, M. & LeCun, Y., 2019.

    Research output: Contribution to conferencePaper

    Entropy-SGD: Biasing gradient descent into wide valleys (International Conference on Learning Representations, ICLR 2017)

    Chaudhari, P., Choromanska, A., Soatto, S., LeCun, Y., Baldassi, C., Borgs, C., Chayes, J., Sagun, L. & Zecchina, R., 2019.

    Research output: Contribution to conferencePaper

    Entropy-SGD: Biasing gradient descent into wide valleys

    Chaudhari, P., Choromanska, A., Soatto, S., Lecun, Y., Baldassi, C., Borgs, C., Chayes, J., Sagun, L. & Zecchina, R., Dec 20 2019, In : Journal of Statistical Mechanics: Theory and Experiment. 2019, 12, 124018.

    Research output: Contribution to journalArticle

    Entropy-SGD: Biasing gradient descent into wide valleys. International Conference on Learning Representations (ICLR) 2017

    Chaudhari, P., Choromanska, A., Soatto, S., LeCun, Y., Baldassi, C., Borgs, C., Chayes, J., Sagun, L. & Zecchina, R., Jan 1 2019.

    Research output: Contribution to conferencePaper

    Model-predictive policy learning with uncertainty regularization for driving in dense traffic

    Henaff, M., LeCun, Y. & Canziani, A., Jan 1 2019.

    Research output: Contribution to conferencePaper

    The role of over-parametrization in generalization of neural networks

    Neyshabur, B., Li, Z., Bhojanapalli, S., LeCun, Y. & Srebro, N., Jan 1 2019.

    Research output: Contribution to conferencePaper

    Tracking the world state with recurrent entity networks

    Henaff, M., Weston, J., Szlam, A., Bordes, A. & LeCun, Y., Jan 1 2019.

    Research output: Contribution to conferencePaper

    Unsupervised image matching and object discovery as optimization

    Vo, H. V., Bach, F., Cho, M., Han, K., Lecun, Y., Perez, P. & Ponce, J., Jun 2019, Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019. IEEE Computer Society, p. 8279-8288 10 p. 8953281. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; vol. 2019-June).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2018

    A Closer Look at Spatiotemporal Convolutions for Action Recognition

    Tran, D., Wang, H., Torresani, L., Ray, J., Lecun, Y. & Paluri, M., Dec 14 2018, Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018. IEEE Computer Society, p. 6450-6459 10 p. 8578773. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Adversarially regularized autoencoders

    Zhao, J., Kim, Y., Zhang, K., Rush, A. M. & LeCun, Y., 2018, 35th International Conference on Machine Learning, ICML 2018. Krause, A. & Dy, J. (eds.). International Machine Learning Society (IMLS), p. 9405-9420 16 p. (35th International Conference on Machine Learning, ICML 2018; vol. 13).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Comparing Dynamics: Deep Neural Networks versus Glassy Systems

    Baity-Jest, M., Sagun, L., Mario, G., Spiglery, S., Arous, G. B., Cammarota, C., Lecun, Y., Vvyart, M. & Biroli, G. J., 2018, 35th International Conference on Machine Learning, ICML 2018. Krause, A. & Dy, J. (eds.). International Machine Learning Society (IMLS), p. 526-535 10 p. (35th International Conference on Machine Learning, ICML 2018; vol. 1).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    GloMO: Unsupervised learning of transferable relational graphs

    Yang, Z., Zhao, J., Dhingra, B., He, K., Cohen, W. W., Salakhutdinov, R. & LeCun, Y., 2018, In : Advances in Neural Information Processing Systems. 2018-December, p. 8950-8961 12 p.

    Research output: Contribution to journalConference article

    Predicting future instance segmentation by forecasting convolutional features

    Luc, P., Couprie, C., LeCun, Y. & Verbeek, J., 2018, Computer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings. Hebert, M., Ferrari, V., Sminchisescu, C. & Weiss, Y. (eds.). Springer Verlag, p. 593-608 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11213 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Universal halting times in optimization and machine learning

    Sagun, L., Trogdon, T. & Lecun, Y., 2018, In : Quarterly of Applied Mathematics. 76, 2, p. 289-301 13 p.

    Research output: Contribution to journalArticle

    2017

    Geometric Deep Learning: Going beyond Euclidean data

    Bronstein, M. M., Bruna, J., Lecun, Y., Szlam, A. & Vandergheynst, P., Jul 2017, In : IEEE Signal Processing Magazine. 34, 4, p. 18-42 25 p., 7974879.

    Research output: Contribution to journalReview article

    Predicting Deeper into the Future of Semantic Segmentation

    Luc, P., Neverova, N., Couprie, C., Verbeek, J. & Lecun, Y., Dec 22 2017, Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017. Institute of Electrical and Electronics Engineers Inc., p. 648-657 10 p. 8237339. (Proceedings of the IEEE International Conference on Computer Vision; vol. 2017-October).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Tunable efficient unitary neural networks (EUNN) and their application to RNNs

    Jing, L., Shen, Y., Dubcek, T., Peurifoy, J., Skirlo, S., LeCun, Y., Tegmark, M. & Soljačić, M., 2017, 34th International Conference on Machine Learning, ICML 2017. International Machine Learning Society (IMLS), p. 2753-2761 9 p. (34th International Conference on Machine Learning, ICML 2017; vol. 4).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Universum prescription: Regularization using unlabeled data

    Zhang, X. & LeCun, Y., 2017, p. 2907-2913. 7 p.

    Research output: Contribution to conferencePaper

    Very deep convolutional networks for text classification

    Conneau, A., Schwenk, H., Cun, Y. L. & Barrault, L., 2017, Long Papers - Continued. Association for Computational Linguistics (ACL), p. 1107-1116 10 p. (15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference; vol. 1).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2016

    A mathematical motivation for complex-valued convolutional networks

    Tygert, M., Bruna, J., Chintala, S., LeCun, Y., Piantino, S. & Szlam, A., May 1 2016, In : Neural computation. 28, 5, p. 815-825 11 p.

    Research output: Contribution to journalArticle

    Binary embeddings with structured hashed projections

    Choromanska, A., Choromanski, K., Bojarski, M., Jebara, T., Kumar, S. & Lecun, Y., 2016, 33rd International Conference on Machine Learning, ICML 2016. Balcan, M. F. & Weinberger, K. Q. (eds.). International Machine Learning Society (IMLS), p. 539-554 16 p. (33rd International Conference on Machine Learning, ICML 2016; vol. 1).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Deep learning & convolutional networks

    LeCun, Y., May 23 2016, 2015 IEEE Hot Chips 27 Symposium, HCS 2015. Institute of Electrical and Electronics Engineers Inc., 7477328. (2015 IEEE Hot Chips 27 Symposium, HCS 2015).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Deep multi-scale video prediction beyond mean square error

    Mathieu, M., Couprie, C. & LeCun, Y., Jan 1 2016.

    Research output: Contribution to conferencePaper

    Disentangling factors of variation in deep representations using adversarial training

    Mathieu, M., Zhao, J., Sprechmann, P., Ramesh, A. & Le Cun, Y., 2016, In : Advances in Neural Information Processing Systems. p. 5047-5055 9 p.

    Research output: Contribution to journalConference article

    Recurrent orthogonal networks and long-memory tasks

    Henaff, M., Szlam, A. & Lecun, Y., 2016, 33rd International Conference on Machine Learning, ICML 2016. Weinberger, K. Q. & Balcan, M. F. (eds.). International Machine Learning Society (IMLS), p. 2978-2986 9 p. (33rd International Conference on Machine Learning, ICML 2016; vol. 5).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Stereo matching by training a convolutional neural network to compare image patches

    Žbontar, J. & Lecun, Y., Apr 1 2016, In : Journal of Machine Learning Research. 17

    Research output: Contribution to journalArticle

    Super-resolution with deep convolutional sufficient statistics

    Bruna, J., Sprechmann, P. & LeCun, Y., Jan 1 2016.

    Research output: Contribution to conferencePaper

    Very deep multilingual convolutional neural networks for LVCSR

    Sercu, T., Puhrsch, C., Kingsbury, B. & Lecun, Y., May 18 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 4955-4959 5 p. 7472620. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; vol. 2016-May).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2015

    Audio source separation with discriminative scattering networks

    Sprechmann, P., Bruna, J. & LeCun, Y., 2015, Latent Variable Analysis and Signal Separation - 12th International Conference, LVA/ICA 2015, Proceedings. Koldovský, Z., Vincent, E., Yeredor, A. & Tichavský, P. (eds.). Springer Verlag, p. 259-267 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9237).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Character-level convolutional networks for text classification

    Zhang, X., Zhao, J. & Lecun, Y., 2015, In : Advances in Neural Information Processing Systems. 2015-January, p. 649-657 9 p.

    Research output: Contribution to journalConference article

    Computing the stereo matching cost with a convolutional neural network

    Žbontar, J. & Le Cun, Y., Oct 14 2015, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015. IEEE Computer Society, p. 1592-1599 8 p. 7298767. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; vol. 07-12-June-2015).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Convolutional nets and watershed cuts for real-time semantic labeling of RGBD videos

    Couprie, C., Farabet, C., Najman, L. & LeCun, Y., Jan 1 2015, In : Journal of Machine Learning Research. 15, p. 3489-3511 23 p., A20.

    Research output: Contribution to journalArticle

    Deep learning

    Lecun, Y., Bengio, Y. & Hinton, G., May 27 2015, In : Nature. 521, 7553, p. 436-444 9 p.

    Research output: Contribution to journalReview article

    Deep learning with elastic averaging SGD

    Zhang, S., Choromanska, A. & Lecun, Y., 2015, In : Advances in Neural Information Processing Systems. 2015-January, p. 685-693 9 p.

    Research output: Contribution to journalConference article

    Deep learning with elastic averaging SGD

    Zhang, S., Choromanska, A. & LeCun, Y., 2015.

    Research output: Contribution to conferencePaper

    Efficient object localization using convolutional networks

    Lecun, Y., 2015, Computer vision and pattern recognition (CVPR 2015).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Explorations on high dimensional landscapes

    Sagun, L., Ugur Güney, V., Arous, G. B. & LeCun, Y., Jan 1 2015.

    Research output: Contribution to conferencePaper

    Fast convolutional nets with fbfft: A GPU performance evaluation

    Vasilache, N., Johnson, J., Mathieu, M., Chintala, S., Piantino, S. & LeCun, Y., Jan 1 2015.

    Research output: Contribution to conferencePaper

    Guest Editorial: Deep Learning

    Ranzato, MA. A., Hinton, G. & LeCun, Y., May 1 2015, In : International Journal of Computer Vision. 113, 1, p. 1-2 2 p.

    Research output: Contribution to journalEditorial

    Learning to linearize under uncertainty

    Goroshin, R., Mathieu, M. & Lecun, Y., 2015, In : Advances in Neural Information Processing Systems. 2015-January, p. 1234-1242 9 p.

    Research output: Contribution to journalConference article

    MoDeep: A deep learning framework using motion features for human pose estimation

    Jain, A., Tompson, J., LeCun, Y. & Bregler, C., 2015, Computer Vision - ACCV 2014 - 12th Asian Conference on Computer Vision, Revised Selected Papers. Yang, M-H., Saito, H., Cremers, D. & Reid, I. (eds.). Springer Verlag, p. 302-315 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9004).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Source separation with scattering Non-Negative Matrix Factorization

    Bruna, J., Sprechmann, P. & Lecun, Y., Aug 4 2015, 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 1876-1880 5 p. 7178296. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; vol. 2015-August).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution