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Yoshua Bengio — all works

122 works · page 2 of 2 · 101–122 · ← Yoshua Bengio

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  1. On the Equivalence between Deep NADE and Generative Stochastic Networks ↗Lecture notes in computer science · no summary yetLi Yao et al.2014 · 10 citations
  2. Boundary Seeking GANs ↗International Conference on Learning Representations · no summary yetR Devon Hjelm et al.2018 · 7 citations
  3. Empirical performance upper bounds for image and video captioning ↗arXiv (Cornell University) · no summary yetLi Yao et al.2015 · 6 citations
  4. Learned-norm pooling for deep neural networks. ↗arXiv (Cornell University) · no summary yetÇağlar Gülçehre et al.2013 · 6 citations
  5. Task Loss Estimation for Structured Prediction ↗no summary yetDzmitry Bahdanau et al.2016 · 5 citations
  6. Combating False Negatives in Adversarial Imitation Learning ↗arXiv:2002.00412 · no summary yetKonrad Żołna et al.2021 · 4 citations
  7. MixupE: Understanding and Improving Mixup from Directional Derivative Perspective ↗arXiv (Cornell University) · no summary yetZou, Yingtian et al.2022 · 2 citations
  8. Automated curriculum generation for Policy Gradients from Demonstrations ↗arXiv (Cornell University) · no summary yetAnirudh Srinivasan et al.2019 · 2 citations
  9. Deep Learning for NLP (without Magic) References ↗no summary yetRichard Socher, Yoshua Bengio, Christopher D. Manning2012 · 2 citations
  10. Neural Bayes: A Generic Parameterization Method for Unsupervised Representation Learning ↗arXiv (Cornell University) · no summary yetDevansh Arpit et al.2020 · 1 citation
  11. Combating False Negatives in Adversarial Imitation Learning (Student Abstract) ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetKonrad Żołna et al.2020 · 1 citation
  12. Approche statistique pour le repérage de mots informatifs dans les textes oraux ↗Actes de la 11ème conférence sur le Traitement Automatique des Langues Naturelles. Articles longs · no summary yetNarjès Boufaden, Yoshua Bengio, Guy Lapalme2004 · 1 citation
  13. When Benign Inputs Lead to Severe Harms: Eliciting Unsafe Unintended Behaviors of Computer-Use Agents ↗arXiv (Cornell University) · no summary yetJaylen Jones et al.2026
  14. Proceedings of the Workshop on Generalization in the Age of Deep Learning ↗Greater South Information System · no summary yetSoumya Wadhwa et al.2018
  15. エンドツーエンド注意に基づいた大語い音声認識【Powered by NICT】 ↗IEEE Conference Proceedings · no summary yetDzmitry Bahdanau et al.2016
  16. How to construct deep recurrent neural networks. arXiv preprint arXiv:1312.6026, 2013. Polyak, Boris Teodorovich. Some methods of speeding up the convergence of iteration methods ↗no summary yetRazvan Pascanu et al.2016
  17. ReSeg:意味論的セグメンテーションのためのリカレントニューラルネットワークに基づくモデル【Powered by NICT】 ↗IEEE Conference Proceedings · no summary yetFrancesco Visin et al.2016
  18. Learning phrase representations using rnn encoderdecoder for statistical machine translation. arXiv preprint arXiv:1406.1078 ↗no summary yetKyunghyun Cho et al.2014
  19. Iterative Neural Autoregressive Distribution Estimator (NADE-k)”. Accepted to ↗no summary yetTapani Raiko et al.2014
  20. Six Reasons to Explore Deep Learning ↗no summary yetRichard Socher et al.2014
  21. and their parts ↗no summary yetMach Learn et al.2012
  22. Segmentation en thèmes de conversations téléphoniques : traitement en amont pour l'extraction d'information ↗Actes de la 9ème conférence sur le Traitement Automatique des Langues Naturelles. Posters · no summary yetNarjès Boufaden, Guy Lapalme, Yoshua Bengio2002

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