| Year |
Citation |
Score |
| 2021 |
Verma V, Kawaguchi K, Lamb A, Kannala J, Solin A, Bengio Y, Lopez-Paz D. Interpolation consistency training for semi-supervised learning. Neural Networks : the Official Journal of the International Neural Network Society. 145: 90-106. PMID 34735894 DOI: 10.1016/j.neunet.2021.10.008 |
0.356 |
|
| 2021 |
Lao Q, Jiang X, Havaei M, Bengio Y. A Two-Stream Continual Learning System With Variational Domain-Agnostic Feature Replay. Ieee Transactions On Neural Networks and Learning Systems. PMID 33657001 DOI: 10.1109/TNNLS.2021.3057453 |
0.311 |
|
| 2020 |
Cohen JP, Dao L, Roth K, Morrison P, Bengio Y, Abbasi AF, Shen B, Mahsa HK, Ghassemi M, Li H, Duong T. Predicting COVID-19 Pneumonia Severity on Chest X-ray With Deep Learning. Cureus. 12: e9448. PMID 32864270 DOI: 10.7759/Cureus.9448 |
0.311 |
|
| 2020 |
Trofimov A, Cohen JP, Bengio Y, Perreault C, Lemieux S. Factorized embeddings learns rich and biologically meaningful embedding spaces using factorized tensor decomposition. Bioinformatics (Oxford, England). 36: i417-i426. PMID 32657403 DOI: 10.1093/Bioinformatics/Btaa488 |
0.332 |
|
| 2020 |
Luccioni A, Bengio Y. On the Morality of Artificial Intelligence [Commentary] Ieee Technology and Society Magazine. 39: 16-25. DOI: 10.1109/Mts.2020.2967486 |
0.424 |
|
| 2020 |
Bengio Y, Lodi A, Prouvost A. Machine learning for combinatorial optimization: A methodological tour d’horizon European Journal of Operational Research. DOI: 10.1016/J.Ejor.2020.07.063 |
0.439 |
|
| 2019 |
Sodhani S, Chandar S, Bengio Y. Toward Training Recurrent Neural Networks for Lifelong Learning. Neural Computation. 1-34. PMID 31703175 DOI: 10.1162/Neco_A_01246 |
0.486 |
|
| 2019 |
Richards BA, Lillicrap TP, Beaudoin P, Bengio Y, Bogacz R, Christensen A, Clopath C, Costa RP, de Berker A, Ganguli S, Gillon CJ, Hafner D, Kepecs A, Kriegeskorte N, Latham P, et al. A deep learning framework for neuroscience. Nature Neuroscience. 22: 1761-1770. PMID 31659335 DOI: 10.1038/S41593-019-0520-2 |
0.411 |
|
| 2019 |
Kawaguchi K, Bengio Y. Depth with nonlinearity creates no bad local minima in ResNets. Neural Networks : the Official Journal of the International Neural Network Society. 118: 167-174. PMID 31295691 DOI: 10.1016/J.Neunet.2019.06.009 |
0.401 |
|
| 2019 |
Jing L, Gulcehre C, Peurifoy J, Shen Y, Tegmark M, Soljacic M, Bengio Y. Gated Orthogonal Recurrent Units: On Learning to Forget. Neural Computation. 1-19. PMID 30764742 DOI: 10.1162/Neco_A_01174 |
0.347 |
|
| 2019 |
Scellier B, Bengio Y. Equivalence of Equilibrium Propagation and Recurrent Backpropagation. Neural Computation. 31: 312-329. PMID 30576611 DOI: 10.1162/Neco_A_01160 |
0.332 |
|
| 2019 |
Thompson J, Bengio Y, Schoenwiesner M. The effect of task and training on intermediate representations in convolutional neural networks revealed with modified RV similarity analysis Arxiv: Learning. DOI: 10.32470/Ccn.2019.1300-0 |
0.37 |
|
| 2019 |
Francois-Lavet V, Bengio Y, Precup D, Pineau J. Combined Reinforcement Learning via Abstract Representations Proceedings of the Aaai Conference On Artificial Intelligence. 33: 3582-3589. DOI: 10.1609/aaai.v33i01.33013582 |
0.326 |
|
| 2018 |
Derevyanko G, Grudinin S, Bengio Y, Lamoureux G. Deep convolutional networks for quality assessment of protein folds. Bioinformatics (Oxford, England). PMID 29931128 DOI: 10.1093/Bioinformatics/Bty494 |
0.333 |
|
| 2018 |
Gulcehre C, Chandar S, Cho K, Bengio Y. Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes. Neural Computation. 1-28. PMID 29381440 DOI: 10.1162/Neco_A_01060 |
0.397 |
|
| 2018 |
Dumoulin V, Perez E, Schucher N, Strub F, Vries H, Courville A, Bengio Y. Feature-wise transformations Distill. 3. DOI: 10.23915/DISTILL.00011 |
0.611 |
|
| 2018 |
Ravanelli M, Brakel P, Omologo M, Bengio Y. Light Gated Recurrent Units for Speech Recognition Ieee Transactions On Emerging Topics in Computational Intelligence. 2: 92-102. DOI: 10.1109/Tetci.2017.2762739 |
0.392 |
|
| 2017 |
Drozdzal M, Chartrand G, Vorontsov E, Shakeri M, Di Jorio L, Tang A, Romero A, Bengio Y, Pal C, Kadoury S. Learning normalized inputs for iterative estimation in medical image segmentation. Medical Image Analysis. 44: 1-13. PMID 29169029 DOI: 10.1016/J.Media.2017.11.005 |
0.306 |
|
| 2017 |
Scellier B, Bengio Y. Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation. Frontiers in Computational Neuroscience. 11: 24. PMID 28522969 DOI: 10.3389/Fncom.2017.00024 |
0.373 |
|
| 2017 |
Zhang XY, Yin F, Zhang YM, Liu CL, Bengio Y. Drawing and Recognizing Chinese Characters with Recurrent Neural Network. Ieee Transactions On Pattern Analysis and Machine Intelligence. PMID 28436845 DOI: 10.1109/Tpami.2017.2695539 |
0.431 |
|
| 2017 |
Zhang X, Xie G, Liu C, Bengio Y. End-to-End Online Writer Identification With Recurrent Neural Network Ieee Transactions On Human-Machine Systems. 47: 285-292. DOI: 10.1109/Thms.2016.2634921 |
0.351 |
|
| 2017 |
Zhang XY, Bengio Y, Liu CL. Online and offline handwritten Chinese character recognition: A comprehensive study and new benchmark Pattern Recognition. 61: 348-360. DOI: 10.1016/J.Patcog.2016.08.005 |
0.453 |
|
| 2017 |
Gulcehre C, Firat O, Xu K, Cho K, Bengio Y. On integrating a language model into neural machine translation Computer Speech & Language. 45: 137-148. DOI: 10.1016/J.Csl.2017.01.014 |
0.361 |
|
| 2017 |
Choi H, Cho K, Bengio Y. Context-dependent word representation for neural machine translation Computer Speech & Language. 45: 149-160. DOI: 10.1016/J.Csl.2017.01.007 |
0.34 |
|
| 2017 |
Firat O, Cho K, Sankaran B, Yarman Vural FT, Bengio Y. Multi-way, multilingual neural machine translation Computer Speech & Language. 45: 236-252. DOI: 10.1016/J.Csl.2016.10.006 |
0.344 |
|
| 2017 |
Hill F, Cho K, Jean S, Bengio Y. The representational geometry of word meanings acquired by neural machine translation models Machine Translation. 31: 3-18. DOI: 10.1007/S10590-017-9194-2 |
0.401 |
|
| 2016 |
Havaei M, Davy A, Warde-Farley D, Biard A, Courville A, Bengio Y, Pal C, Jodoin PM, Larochelle H. Brain tumor segmentation with Deep Neural Networks. Medical Image Analysis. 35: 18-31. PMID 27310171 DOI: 10.1016/J.Media.2016.05.004 |
0.714 |
|
| 2016 |
Bengio Y. Machines Who Learn. Scientific American. 314: 46-51. PMID 27196842 DOI: 10.1038/Scientificamerican0616-46 |
0.489 |
|
| 2016 |
Hill F, Cho K, Korhonen A, Bengio Y. Learning to Understand Phrases by Embedding the Dictionary Transactions of the Association For Computational Linguistics. 4: 17-30. DOI: 10.1162/Tacl_A_00080 |
0.43 |
|
| 2016 |
Laurent C, Pereyra G, Brakel P, Zhang Y, Bengio Y. Batch normalized recurrent neural networks Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 2016: 2657-2661. DOI: 10.1109/ICASSP.2016.7472159 |
0.312 |
|
| 2016 |
Alain G, Bengio Y, Yao L, Yosinski J, Thibodeau-Laufer É, Zhang S, Vincent P. GSNs: generative stochastic networks Information and Inference. 5: 210-249. DOI: 10.1093/Imaiai/Iaw003 |
0.664 |
|
| 2016 |
Gülçehre Ç, Bengio Y. Knowledge matters: Importance of prior information for optimization Journal of Machine Learning Research. 17. |
0.383 |
|
| 2015 |
LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 521: 436-44. PMID 26017442 DOI: 10.1038/Nature14539 |
0.442 |
|
| 2015 |
Goodfellow IJ, Erhan D, Luc Carrier P, Courville A, Mirza M, Hamner B, Cukierski W, Tang Y, Thaler D, Lee DH, Zhou Y, Ramaiah C, Feng F, Li R, Wang X, ... ... Bengio Y, et al. Challenges in representation learning: a report on three machine learning contests. Neural Networks : the Official Journal of the International Neural Network Society. 64: 59-63. PMID 25613956 DOI: 10.1016/J.Neunet.2014.09.005 |
0.805 |
|
| 2015 |
Bengio Y, Lee H. Editorial introduction to the Neural Networks special issue on Deep Learning of Representations. Neural Networks : the Official Journal of the International Neural Network Society. 64: 1-3. PMID 25595998 DOI: 10.1016/J.Neunet.2014.12.006 |
0.442 |
|
| 2015 |
Cho K, Courville A, Bengio Y. Describing Multimedia Content Using Attention-Based Encoder-Decoder Networks Ieee Transactions On Multimedia. 17: 1875-1886. DOI: 10.1109/Tmm.2015.2477044 |
0.719 |
|
| 2015 |
Mesnil G, Dauphin Y, Yao K, Bengio Y, Deng L, Hakkani-Tur D, He X, Heck L, Tur G, Yu D, Zweig G. Using recurrent neural networks for slot filling in spoken language understanding Ieee Transactions On Audio, Speech and Language Processing. 23: 530-539. DOI: 10.1109/Taslp.2014.2383614 |
0.357 |
|
| 2015 |
Kahou SE, Bouthillier X, Lamblin P, Gulcehre C, Michalski V, Konda K, Jean S, Froumenty P, Dauphin Y, Boulanger-Lewandowski N, Chandias Ferrari R, Mirza M, Warde-Farley D, Courville A, Vincent P, ... ... Bengio Y, et al. EmoNets: Multimodal deep learning approaches for emotion recognition in video Journal On Multimodal User Interfaces. DOI: 10.1007/S12193-015-0195-2 |
0.771 |
|
| 2015 |
Mesnil G, Rifai S, Bordes A, Glorot X, Bengio Y, Vincent P. Unsupervised learning of semantics of object detections for scene categorization Advances in Intelligent Systems and Computing. 318: 209-224. DOI: 10.1007/978-3-319-12610-4_13 |
0.565 |
|
| 2015 |
Gouws S, Bengio Y, Corrado G. BilBOWA: Fast bilingual distributed representations without word alignments 32nd International Conference On Machine Learning, Icml 2015. 1: 748-756. |
0.305 |
|
| 2015 |
Dauphin YN, De Vries H, Bengio Y. Equilibrated adaptive learning rates for non-convex optimization Advances in Neural Information Processing Systems. 2015: 1504-1512. |
0.334 |
|
| 2015 |
Chung J, Kastner K, Dinh L, Goel K, Courville A, Bengio Y. A recurrent latent variable model for sequential data Advances in Neural Information Processing Systems. 2015: 2980-2988. |
0.659 |
|
| 2015 |
Xu K, Ba JL, Kiros R, Cho K, Courville A, Salakhutdinov R, Zemel RS, Bengio Y. Show, attend and tell: Neural image caption generation with visual attention 32nd International Conference On Machine Learning, Icml 2015. 3: 2048-2057. |
0.332 |
|
| 2014 |
Courville A, Desjardins G, Bergstra J, Bengio Y. The Spike-and-Slab RBM and Extensions to Discrete and Sparse Data Distributions. Ieee Transactions On Pattern Analysis and Machine Intelligence. 36: 1874-87. PMID 26352238 DOI: 10.1109/Tpami.2013.238 |
0.777 |
|
| 2014 |
Rivest F, Kalaska JF, Bengio Y. Conditioning and time representation in long short-term memory networks. Biological Cybernetics. 108: 23-48. PMID 24258005 DOI: 10.1007/S00422-013-0575-1 |
0.337 |
|
| 2014 |
Bordes A, Glorot X, Weston J, Bengio Y. A semantic matching energy function for learning with multi-relational data: Application to word-sense disambiguation Machine Learning. 94: 233-259. DOI: 10.1007/s10994-013-5363-6 |
0.316 |
|
| 2014 |
Mesnil G, Bordes A, Weston J, Chechik G, Bengio Y. Learning semantic representations of objects and their parts Machine Learning. 94: 281-301. DOI: 10.1007/S10994-013-5336-9 |
0.372 |
|
| 2014 |
Raiko T, Yao L, Cho K, Bengio Y. Iterative neural autoregressive distribution estimator (NADE-k) Advances in Neural Information Processing Systems. 1: 325-333. |
0.333 |
|
| 2014 |
Chen M, Weinberger K, Sha F, Bengio Y. Marginalized denoising auto-encoders for nonlinear representations 31st International Conference On Machine Learning, Icml 2014. 4: 3342-3350. |
0.629 |
|
| 2014 |
Bengio Y, Thibodeau-Laufer É, Alain G, Yosinski J. Deep generative stochastic networks trainable by backprop 31st International Conference On Machine Learning, Icml 2014. 2: 1470-1485. |
0.38 |
|
| 2014 |
Dumoulin V, Goodfellow IJ, Courville A, Bengio Y. On the challenges of physical implementations of RBMs Proceedings of the National Conference On Artificial Intelligence. 2: 1199-1205. |
0.669 |
|
| 2014 |
Goodfellow IJ, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y. Generative adversarial nets Advances in Neural Information Processing Systems. 3: 2672-2680. |
0.619 |
|
| 2013 |
Courville A, Desjardins G, Bergstra J, Bengio Y. The Spike-and-Slab RBM and Extensions to Discrete and Sparse Data Distributions. Ieee Transactions On Pattern Analysis and Machine Intelligence. PMID 24323880 |
0.595 |
|
| 2013 |
Goodfellow IJ, Courville A, Bengio Y. Scaling up spike-and-slab models for unsupervised feature learning. Ieee Transactions On Pattern Analysis and Machine Intelligence. 35: 1902-14. PMID 23787343 DOI: 10.1109/Tpami.2012.273 |
0.703 |
|
| 2013 |
Bengio Y, Courville A, Vincent P. Representation learning: a review and new perspectives. Ieee Transactions On Pattern Analysis and Machine Intelligence. 35: 1798-828. PMID 23787338 DOI: 10.1109/Tpami.2013.50 |
0.799 |
|
| 2013 |
Bengio Y, Courville A, Vincent P. Representation Learning: A Review and New Perspectives. Ieee Transactions On Pattern Analysis and Machine Intelligence. PMID 23459267 |
0.638 |
|
| 2013 |
Kahou SE, Pal C, Bouthillier X, Froumenty P, Gülçehre C, Memisevic R, Vincent P, Courville A, Bengio Y, Ferrari RC, Mirza M, Jean S, Carrier PL, Dauphin Y, Boulanger-Lewandowski N, et al. Combining modality specific deep neural networks for emotion recognition in video Icmi 2013 - Proceedings of the 2013 Acm International Conference On Multimodal Interaction. 543-550. DOI: 10.1145/2522848.2531745 |
0.644 |
|
| 2013 |
Martinez HP, Bengio Y, Yannakakis G. Learning deep physiological models of affect Ieee Computational Intelligence Magazine. 8: 20-33. DOI: 10.1109/Mci.2013.2247823 |
0.329 |
|
| 2013 |
Bengio Y, Boulanger-Lewandowski N, Pascanu R. Advances in optimizing recurrent networks Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 8624-8628. DOI: 10.1109/ICASSP.2013.6639349 |
0.311 |
|
| 2013 |
Laufer E, Ferrari RC, Yao L, Delalleau O, Bengio Y. Stacked calibration of off-policy policy evaluation for video game matchmaking Ieee Conference On Computatonal Intelligence and Games, Cig. DOI: 10.1109/CIG.2013.6633642 |
0.74 |
|
| 2013 |
Goodfellow IJ, Erhan D, Carrier PL, Courville A, Mirza M, Hamner B, Cukierski W, Tang Y, Thaler D, Lee DH, Zhou Y, Ramaiah C, Feng F, Li R, Wang X, ... ... Bengio Y, et al. Challenges in representation learning: A report on three machine learning contests Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8228: 117-124. DOI: 10.1007/978-3-642-42051-1_16 |
0.805 |
|
| 2013 |
Bengio Y. Deep learning of representations: Looking forward Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7978: 1-37. DOI: 10.1007/978-3-642-39593-2_1 |
0.352 |
|
| 2013 |
Bengio Y, Courville A. Deep Learning of Representations Intelligent Systems Reference Library. 49: 1-28. DOI: 10.1007/978-3-642-36657-4_1 |
0.73 |
|
| 2013 |
Luo H, Carrier PL, Courville A, Bengio Y. Texture modeling with convolutional spike-and-slab RBMs and deep extensions Journal of Machine Learning Research. 31: 415-423. |
0.661 |
|
| 2013 |
Goodfellow IJ, Mirza M, Courville A, Bengio Y. Multi-prediction deep Boltzmann machines Advances in Neural Information Processing Systems. |
0.71 |
|
| 2013 |
Goodfellow IJ, Warde-Farley D, Mirza M, Courville A, Bengio Y. Maxout networks 30th International Conference On Machine Learning, Icml 2013. 2356-2364. |
0.674 |
|
| 2013 |
Mesnil G, Rifai S, Bordes A, Glorot X, Bengio Y, Vincent P. Unsupervised and transfer learning under uncertainty: From object detections to scene categorization Icpram 2013 - Proceedings of the 2nd International Conference On Pattern Recognition Applications and Methods. 345-354. |
0.561 |
|
| 2012 |
Bengio Y, Chapados N, Delalleau O, Larochelle H, Saint-Mleux X, Hudon C, Louradour J. Detonation classification from acoustic signature with the Restricted Boltzmann Machine Computational Intelligence. 28: 261-288. DOI: 10.1111/j.1467-8640.2012.00419.x |
0.768 |
|
| 2012 |
Delalleau O, Contal E, Thibodeau-Laufer E, Ferrari RC, Bengio Y, Zhang F. Beyond skill rating: Advanced matchmaking in ghost recon online Ieee Transactions On Computational Intelligence and Ai in Games. 4: 167-177. DOI: 10.1109/Tciaig.2012.2188833 |
0.763 |
|
| 2012 |
Bengio Y. Practical recommendations for gradient-based training of deep architectures Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7700: 437-478. DOI: 10.1007/978-3-642-35289-8-26 |
0.354 |
|
| 2012 |
Rifai S, Bengio Y, Courville A, Vincent P, Mirza M. Disentangling factors of variation for facial expression recognition Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7577: 808-822. DOI: 10.1007/978-3-642-33783-3_58 |
0.76 |
|
| 2012 |
Bergstra J, Bengio Y. Random search for hyper-parameter optimization Journal of Machine Learning Research. 13: 281-305. |
0.456 |
|
| 2012 |
Goodfellow IJ, Courville A, Bengio Y. Large-scale feature learning with spike-and-slab sparse coding Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 2: 1439-1446. |
0.728 |
|
| 2012 |
Hamel P, Bengio Y, Eck D. Building musically-relevant audio features through multiple timescale representations Proceedings of the 13th International Society For Music Information Retrieval Conference, Ismir 2012. 553-558. |
0.524 |
|
| 2012 |
Rifai S, Bengio Y, Dauphin YN, Vincent P. A generative process for sampling contractive auto-encoders Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 2: 1855-1862. |
0.35 |
|
| 2012 |
Bordes A, Glorot X, Weston J, Bengio Y. Joint learning of words and meaning representations for open-text semantic parsing Journal of Machine Learning Research. 22: 127-135. |
0.337 |
|
| 2012 |
Larochelle H, Mandel M, Pascanu R, Bengio Y. Learning algorithms for the classification restricted Boltzmann machine Journal of Machine Learning Research. 13: 643-669. |
0.319 |
|
| 2011 |
Bergstra J, Bengio Y, Louradour J. Suitability of V1 energy models for object classification. Neural Computation. 23: 774-90. PMID 21162668 DOI: 10.1162/Neco_A_00084 |
0.61 |
|
| 2011 |
Breuleux O, Bengio Y, Vincent P. Quickly generating representative samples from an RBM-derived process Neural Computation. 23: 2058-2073. DOI: 10.1162/Neco_A_00158 |
0.617 |
|
| 2011 |
Bengio Y, Delalleau O. On the expressive power of deep architectures Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6925: 18-36. DOI: 10.1007/978-3-642-24412-4_3 |
0.778 |
|
| 2011 |
Rifai S, Mesnil G, Vincent P, Muller X, Bengio Y, Dauphin Y, Glorot X. Higher order contractive auto-encoder Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6912: 645-660. DOI: 10.1007/978-3-642-23783-6_41 |
0.574 |
|
| 2011 |
Delalleau O, Bengio Y. Shallow vs. deep sum-product networks Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011. |
0.776 |
|
| 2011 |
Dauphin YN, Glorot X, Bengio Y. Large-scale learning of embeddings with reconstruction sampling Proceedings of the 28th International Conference On Machine Learning, Icml 2011. 945-952. |
0.362 |
|
| 2011 |
Desjardins G, Courville A, Bengio Y. On tracking the partition function Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011. |
0.695 |
|
| 2011 |
Courville A, Bergstra J, Bengio Y. A spike and slab Restricted Boltzmann Machine Journal of Machine Learning Research. 15: 233-241. |
0.749 |
|
| 2011 |
Courville A, Bergstra J, Bengio Y. Unsupervised models of images by spike-and-slab RBMs Proceedings of the 28th International Conference On Machine Learning, Icml 2011. 1145-1152. |
0.703 |
|
| 2011 |
Bergstra J, Bardenet R, Bengio Y, Kégl B. Algorithms for hyper-parameter optimization Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011. |
0.613 |
|
| 2011 |
Hamel P, Lemieux S, Bengio Y, Eck D. Temporal pooling and multiscale learning for automatic annotation and ranking of music audio Proceedings of the 12th International Society For Music Information Retrieval Conference, Ismir 2011. 729-734. |
0.302 |
|
| 2011 |
Bengio Y, Bastien F, Bergeron A, Boulanger-Lewandowski N, Breuel T, Chherawala Y, Cisse M, Côté M, Erhan D, Eustache J, Glorot X, Muller X, Lebeuf SP, Pascanu R, Rifai S, et al. Deep learners benefit more from out-of-distribution examples Journal of Machine Learning Research. 15: 164-172. |
0.683 |
|
| 2010 |
Larochelle H, Bengio Y, Turian J. Tractable multivariate binary density estimation and the restricted Boltzmann forest. Neural Computation. 22: 2285-307. PMID 20569177 DOI: 10.1162/Neco_A_00014 |
0.324 |
|
| 2010 |
Rivest F, Kalaska JF, Bengio Y. Alternative time representation in dopamine models. Journal of Computational Neuroscience. 28: 107-30. PMID 19847635 DOI: 10.1007/S10827-009-0191-1 |
0.454 |
|
| 2010 |
Le Roux N, Bengio Y. Deep belief networks are compact universal approximators Neural Computation. 22: 2192-2207. DOI: 10.1162/Neco.2010.08-09-1081 |
0.4 |
|
| 2010 |
Bengio Y, Delalleau O, Simard C. Decision trees do not generalize to new variations Computational Intelligence. 26: 449-467. DOI: 10.1111/j.1467-8640.2010.00366.x |
0.791 |
|
| 2010 |
Mandel MI, Eck D, Bengio Y. Learning tags that vary within a song Proceedings of the 11th International Society For Music Information Retrieval Conference, Ismir 2010. 399-404. |
0.302 |
|
| 2010 |
Desjardins G, Courville A, Bengio Y, Vincent P, Delalleau O. Parallel tempering for training of restricted Boltzmann Machines Journal of Machine Learning Research. 9: 145-152. |
0.794 |
|
| 2010 |
Erhan D, Courville A, Bengio Y, Vincent P. Why does unsupervised pre-training help deep learning? Journal of Machine Learning Research. 9: 201-208. |
0.747 |
|
| 2010 |
Erhan D, Courville A, Bengio Y, Vincent P. Why does unsupervised pre-training help deep learning? Journal of Machine Learning Research. 9: 201-208. |
0.805 |
|
| 2010 |
Vincent P, Larochelle H, Lajoie I, Bengio Y, Manzagol PA. Stacked denoising autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion Journal of Machine Learning Research. 11: 3371-3408. |
0.374 |
|
| 2009 |
Bengio Y, Delalleau O. Justifying and generalizing contrastive divergence. Neural Computation. 21: 1601-21. PMID 19018704 DOI: 10.1162/Neco.2008.11-07-647 |
0.757 |
|
| 2009 |
Bengio Y. Learning deep architectures for AI Foundations and Trends in Machine Learning. 2: 1-27. DOI: 10.1561/2200000006 |
0.385 |
|
| 2009 |
Larochelle H, Bengio Y, Louradour J, Lamblin P. Exploring strategies for training deep neural networks Journal of Machine Learning Research. 10: 1-40. DOI: 10.1145/1577069.1577070 |
0.44 |
|
| 2009 |
Bengio Y, Louradour J, Collobert R, Weston J. Curriculum learning Acm International Conference Proceeding Series. 382. DOI: 10.1145/1553374.1553380 |
0.303 |
|
| 2009 |
Bergstra J, Bengio Y. Slow, decorrelated features for pretraining complex cell-like networks Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 99-107. |
0.605 |
|
| 2009 |
Erhan D, Manzagol PA, Bengio Y, Bengio S, Vincent P. The difficulty of training deep architectures and the effect of unsupervised pre-training Journal of Machine Learning Research. 5: 153-160. |
0.731 |
|
| 2009 |
Courville AC, Eck D, Bengio Y. An infinite factor model hierarchy via a noisy-or mechanism Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 405-413. |
0.655 |
|
| 2009 |
Dugas C, Bengio Y, Bélisle F, Nadeau C, Garcia R. Incorporating functional knowledge in neural networks Journal of Machine Learning Research. 10: 1239-1262. |
0.697 |
|
| 2008 |
Bengio Y, Senécal JS. Adaptive importance sampling to accelerate training of a neural probabilistic language model Ieee Transactions On Neural Networks. 19: 713-722. PMID 18390314 DOI: 10.1109/Tnn.2007.912312 |
0.385 |
|
| 2008 |
Le Roux N, Bengio Y. Representational power of restricted boltzmann machines and deep belief networks. Neural Computation. 20: 1631-49. PMID 18254699 DOI: 10.1162/Neco.2008.04-07-510 |
0.423 |
|
| 2008 |
Larochelle H, Bengio Y. Classification using discriminative restricted boltzmann machines Proceedings of the 25th International Conference On Machine Learning. 536-543. |
0.393 |
|
| 2008 |
Larochelle H, Erhan D, Bengio Y. Zero-data learning of new tasks Proceedings of the National Conference On Artificial Intelligence. 2: 646-651. |
0.763 |
|
| 2008 |
Vincent P, Larochelle H, Bengio Y, Manzagol PA. Extracting and composing robust features with denoising autoencoders Proceedings of the 25th International Conference On Machine Learning. 1096-1103. |
0.397 |
|
| 2007 |
Bengio Y. On the challenge of learning complex functions. Progress in Brain Research. 165: 521-34. PMID 17925268 DOI: 10.1016/S0079-6123(06)65033-4 |
0.491 |
|
| 2007 |
Chapados N, Bengio Y. Noisy K best-paths for approximate dynamic programming with application to portfolio optimization Journal of Computers. 2: 12-19. DOI: 10.4304/Jcp.2.1.12-19 |
0.376 |
|
| 2007 |
Larochelle H, Erhan D, Courville A, Bergstra J, Bengio Y. An empirical evaluation of deep architectures on problems with many factors of variation Acm International Conference Proceeding Series. 227: 473-480. DOI: 10.1145/1273496.1273556 |
0.812 |
|
| 2007 |
Bengio Y, Lamblin P, Popovici D, Larochelle H. Greedy layer-wise training of deep networks Advances in Neural Information Processing Systems. 153-160. |
0.319 |
|
| 2006 |
Bengio Y, Monperrus M, Larochelle H. Nonlocal estimation of manifold structure. Neural Computation. 18: 2509-28. PMID 16907635 DOI: 10.1162/Neco.2006.18.10.2509 |
0.453 |
|
| 2006 |
Erhan D, L'heureux PJ, Yue SY, Bengio Y. Collaborative filtering on a family of biological targets. Journal of Chemical Information and Modeling. 46: 626-35. PMID 16562992 DOI: 10.1021/Ci050367T |
0.733 |
|
| 2006 |
Chapados N, Bengio Y. The K best-paths approach to approximate dynamic programming with application to portfolio optimization Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4013: 491-502. DOI: 10.1007/11766247_42 |
0.38 |
|
| 2006 |
Bengio Y, Delalleau O, Le Roux N, Paiement JF, Vincent P, Ouimet M. Spectral dimensionality reduction Studies in Fuzziness and Soft Computing. 207: 519-550. |
0.747 |
|
| 2005 |
Grandvalet Y, Bengio Y. Semi-supervised learning by entropy minimization Advances in Neural Information Processing Systems. |
0.321 |
|
| 2005 |
Bengio Y, Monperrus M. Non-local manifold tangent learning Advances in Neural Information Processing Systems. |
0.342 |
|
| 2005 |
Delalleau O, Bengio Y, Le Roux N. Efficient non-parametric function induction in semi-supervised learning Aistats 2005 - Proceedings of the 10th International Workshop On Artificial Intelligence and Statistics. 96-103. |
0.788 |
|
| 2005 |
Bengio Y, Delalleau O, Le Roux N. The curse of highly variable functions for local kernel machines Advances in Neural Information Processing Systems. 107-114. |
0.747 |
|
| 2005 |
Bengio Y, Le Roux N, Vincent P, Delalleau O, Marcotte P. Convex neural networks Advances in Neural Information Processing Systems. 123-130. |
0.747 |
|
| 2004 |
L'Heureux PJ, Carreau J, Bengio Y, Delalleau O, Yue SY. Locally linear embedding for dimensionality reduction in QSAR. Journal of Computer-Aided Molecular Design. 18: 475-82. PMID 15729847 DOI: 10.1007/S10822-004-5319-9 |
0.759 |
|
| 2004 |
Bengio Y, Delalleau O, Le Roux N, Paiement JF, Vincent P, Ouimet M. Learning eigenfunctions links spectral embedding and kernel PCA. Neural Computation. 16: 2197-219. PMID 15333211 DOI: 10.1162/0899766041732396 |
0.814 |
|
| 2004 |
Bengio Y, Paiement JF, Vincent P, Delalleau O, Le Roux N, Ouimet M. Out-of-sample extensions for LLE, Isomap, MDS, Eigenmaps, and spectral clustering Advances in Neural Information Processing Systems. |
0.721 |
|
| 2003 |
Ghosn J, Bengio Y. Bias learning, knowledge sharing. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 14: 748-65. PMID 18238057 DOI: 10.1109/Tnn.2003.810608 |
0.667 |
|
| 2002 |
Takeuchi I, Bengio Y, Kanamori T. Robust regression with asymmetric heavy-tail noise distributions. Neural Computation. 14: 2469-96. PMID 12396571 DOI: 10.1162/08997660260293300 |
0.347 |
|
| 2002 |
Vincent P, Bengio Y. Kernel matching pursuit Machine Learning. 48: 165-187. DOI: 10.1023/A:1013955821559 |
0.637 |
|
| 2002 |
Chapelle O, Vapnik V, Bengio Y. Model selection for small sample regression Machine Learning. 48: 9-23. DOI: 10.1023/A:1013943418833 |
0.392 |
|
| 2002 |
Collobert R, Bengio Y, Bengio S. Scaling large learning problems with hard parallel mixtures Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2388: 8-23. DOI: 10.1007/3-540-45665-1_2 |
0.478 |
|
| 2002 |
Chapados N, Bengio Y, Vincent P, Ghosn J, Dugas C, Takeuchi I, Meng L. Estimating car insurance premia: A case study in high-dimensional data inference Advances in Neural Information Processing Systems. |
0.752 |
|
| 2001 |
Bengio Y, Ducharme R, Vincent P. A neural probabilistic language model Advances in Neural Information Processing Systems. DOI: 10.1162/153244303322533223 |
0.601 |
|
| 2001 |
Chapados N, Bengio Y. Cost functions and model combination for VaR-based asset allocation using neural networks Ieee Transactions On Neural Networks. 12: 890-906. DOI: 10.1109/72.935098 |
0.36 |
|
| 2001 |
Bengio Y, Lauzon VP, Ducharme R. Experiments on the application of IOHMMs to model financial returns series Ieee Transactions On Neural Networks. 12: 113-123. DOI: 10.1109/72.896800 |
0.336 |
|
| 2001 |
Dugas C, Bengio Y, Bélisle F, Nadeau C, Garcia R. Incorporating second-order functional knowledge for better option pricing Advances in Neural Information Processing Systems. |
0.691 |
|
| 2000 |
Bengio Y. Gradient-based optimization of hyperparameters Neural Computation. 12: 1889-1900. PMID 10953243 DOI: 10.1162/089976600300015187 |
0.392 |
|
| 2000 |
Schwenk H, Bengio Y. Boosting neural networks Neural Computation. 12: 1869-1887. PMID 10953242 DOI: 10.1162/089976600300015178 |
0.445 |
|
| 2000 |
Bengio S, Bengio Y. Taking on the curse of dimensionality in joint distributions using neural networks Ieee Transactions On Neural Networks. 11: 550-557. DOI: 10.1109/72.846725 |
0.361 |
|
| 1999 |
Bengio S, Bengio Y, Robert J, Bélanger G. Stochastic learning of strategic equilibria for auctions Neural Computation. 11: 1199-1209. DOI: 10.1162/089976699300016412 |
0.444 |
|
| 1998 |
LeCun Y, Bottou L, Bengio Y, Haffner P. Gradient-based learning applied to document recognition Proceedings of the Ieee. 86: 2278-2323. DOI: 10.1109/5.726791 |
0.326 |
|
| 1997 |
Bengio Y. Using a financial training criterion rather than a prediction criterion International Journal of Neural Systems. 8: 433-443. PMID 9730019 DOI: 10.1142/S0129065797000422 |
0.392 |
|
| 1997 |
Schwenk H, Bengio Y. Adaboosting neural networks: Application to on-line character recognition Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1327: 967-972. |
0.393 |
|
| 1997 |
Ghosn J, Bengio Y. Multi-task learning for stock selection Advances in Neural Information Processing Systems. 946-952. |
0.614 |
|
| 1996 |
Bengio Y, Frasconi P. Input-output HMM's for sequence processing Ieee Transactions On Neural Networks. 7: 1231-1249. DOI: 10.1109/72.536317 |
0.401 |
|
| 1995 |
Bengio Y, LeCun Y, Nohl C, Burges C. LeRec: a NN/HMM hybrid for on-line handwriting recognition. Neural Computation. 7: 1289-303. PMID 7584903 DOI: 10.1162/Neco.1995.7.6.1289 |
0.316 |
|
| 1995 |
Bengio Y, Frasconi P. Diffusion of Context and Credit Information in Markovian Models Journal of Artificial Intelligence Research. 3: 249-270. DOI: 10.1613/Jair.233 |
0.392 |
|
| 1995 |
Bengio S, Bengio Y, Cloutier J. On the search for new learning rules for ANNs Neural Processing Letters. 2: 26-30. DOI: 10.1007/Bf02279935 |
0.449 |
|
| 1994 |
Bengio Y, Simard P, Frasconi P. Learning Long-Term Dependencies with Gradient Descent is Difficult Ieee Transactions On Neural Networks. 5: 157-166. DOI: 10.1109/72.279181 |
0.443 |
|
| 1993 |
BENGIO Y. A CONNECTIONIST APPROACH TO SPEECH RECOGNITION International Journal of Pattern Recognition and Artificial Intelligence. 7: 647-667. DOI: 10.1142/S0218001493000327 |
0.385 |
|
| 1992 |
Bengio Y, De Mori R, Flammia G, Kompe R. Global Optimization of a Neural Network-Hidden Markov Model Hybrid Ieee Transactions On Neural Networks. 3: 252-259. DOI: 10.1109/72.125866 |
0.361 |
|
| 1992 |
Bengio Y, De Mori R, Gori M. Learning the dynamic nature of speech with back-propagation for sequences Pattern Recognition Letters. 13: 375-385. DOI: 10.1016/0167-8655(92)90035-X |
0.423 |
|
| 1992 |
Bengio Y, De Mori R, Flammia G, Kompe R. Phonetically motivated acoustic parameters for continuous speech recognition using artificial neural networks Speech Communication. 11: 261-271. DOI: 10.1016/0167-6393(92)90020-8 |
0.363 |
|
| 1991 |
Bengio Y, Mori RD. Connectionist Models and their Application to Automatic Speech Recognition Machine Intelligence and Pattern Recognition. 11: 175-194. DOI: 10.1016/B978-0-444-88740-5.50015-3 |
0.444 |
|
| 1990 |
Cosi P, Bengio Y, De Mori R. Phonetically-based multi-layered neural networks for vowel classification Speech Communication. 9: 15-29. DOI: 10.1016/0167-6393(90)90041-7 |
0.428 |
|
| 1989 |
Bengio Y, Cardin R, De Mori R, Merlo E. Programmable execution of multi-layered networks for automatic speech recognition Communications of the Acm. 32: 195-199. DOI: 10.1145/63342.63345 |
0.388 |
|
| Show low-probability matches. |