Joan bruna

joan bruna

allwomenstalk.xyz statb. Topics Course on Deep Learning for Spring by Joan Bruna, UC Berkeley, Statistics Department. ##Syllabus. The latest Tweets from joan bruna (@ joanbruna): "Plasmonic wood rocks! http://t. co/oxw00Qmtid". I am a Ph.D. student at CMAP, École Polytechnique, under the supervision of Professor Stéphane Mallat. My PhD focuses on the construction of invariant signal. Audio texture synthesis with scattering moments J Bruna, S Mallat arXiv preprint arXiv: My current website is western union karte. Dates and citation counts are estimated and are determined automatically by a computer program. We have just created a new research group: Connections with other models: Global Optimality in Tensor Factorization, Deep Learning and Beyond Haefflele, Vidal. Proceedings of the IEEE International Conference on Computer Vision, , Merged citations This "Cited by" count includes citations to the following articles in Scholar. Scholar Get my own profile. Assistant Professor, Courant Institute of Mathematical Sciences, New York University. Invariant scattering convolution networks J Bruna, S Mallat IEEE transactions on pattern analysis and machine intelligence 35 8 , , Merged citations This "Cited by" count includes citations to the following articles in Scholar. Title 1—20 Cited by Year Intriguing properties of neural networks C Szegedy, W Zaremba, I Sutskever, J Bruna, D Erhan, I Goodfellow, Self-supervised models analogies, video prediction, text, word2vec. We have just created a new research group: Exploiting linear structure within convolutional networks for efficient evaluation EL Denton, W Zaremba, J Bruna, Y LeCun, R Fergus Advances in Neural Information Processing Systems, , Assistant Professor, Courant Institute of Mathematical Sciences, New York University. Feb 10, lec7. I am currently on leave from UC Berkeley Statistics Department. Sorry, some features may not work in this version of Internet Explorer. I am currently on leave from UC Berkeley Statistics Department. My research interests touch several areas of Machine Learning, Signal Processing and High-Dimensional Statistics. Convolutional Neural Networks Invariance, stability. Bengio Graphical Models, Exponential Families and Variational Inference M.

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Geometry and first Properties. Scattering representations for recognition J Bruna Ecole Polytechnique X , Joan Bruna Courant Institute of Mathematical Sciences and Center for Data Science, NYU Department of Computer Science, Department of Mathematics affiliated e-mail: Learning stable group invariant representations with convolutional networks J Bruna, A Szlam, Y LeCun arXiv preprint arXiv: Proceedings of the IEEE International Conference on Computer Vision, , Duplicate citations The following articles are merged in Scholar. Spectral networks and locally connected networks on graphs J Bruna, W Zaremba, A Szlam, Y LeCun arXiv preprint arXiv: Co-authors View all… Yann LeCun , Stephane Mallat , Rob Fergus , Arthur Szlam , Wojciech Zaremba , Christian Szegedy , Ilya Sutskever , Dumitru Erhan , Ian Goodfellow , Emily Denton , Jonathan Tompson , Ross Goroshin , Pablo Sprechmann , Marc'Aurelio Ranzato , Ronan Collobert , Michael Mathieu , Sumit Chopra , Soumith Chintala , Mark Tygert , Mikael Henaff. Unsupervised learning of spatiotemporally coherent metrics R Goroshin, J Bruna, J Tompson, D Eigen, Y LeCun Proceedings of the IEEE International Conference on Computer Vision, , Unsupervised feature learning from temporal data R Goroshin, J Bruna, J Tompson, D Eigen, Y LeCun arXiv preprint arXiv: Haussler Improving the Fisher Kernel for Large-Scale Image Classification F. Proceedings of the IEEE International Conference on Computer Vision, , Train Faster, Generalize Better: Their combined citations are counted only for the first article.

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