Documents publiés en "2019"

Article de revue

Anbil Parthipan, S. C., Sankar, C., Vorontsov, E., Kahou, S. E., & Bengio, Y. (2019). Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies. AAAI Conference on Artificial Intelligence, 33(1), 3280-3287. Lien externe

Sodhani, S., Anbil Parthipan, S. C., & Bengio, Y. (2019). Toward Training Recurrent Neural Networks for Lifelong Learning. Neural Computation, 32(1), 1-35. Lien externe

Communication écrite

Pahuja, V., Fu, J., Anbil Parthipan, S. C., & Pal, C. J. (novembre 2019). Structure Learning for Neural Module Networks [Communication écrite]. Beyond Vision and LANguage: inTEgrating Real-world kNowledge (LANTERN 2019), Hong Kong (10 pages). Lien externe

Prato, G., Duchesneau, M., Anbil Parthipan, S. C., & Tapp, A. (juillet 2019). Towards Lossless Encoding of Sentences [Communication écrite]. 57th annual meeting of the Association for Computational Linguistics (ACL), Florence, Italy. Lien externe

Reddy, R., Anbil Parthipan, S. C., & Ravindran, B. (mai 2019). Edge Replacement Grammars : A Formal Language Approach for Generating Graphs [Communication écrite]. SIAM International Conference on Data Mining (SDM 2019), Calgary, AB, Canada. Lien externe

Sankar, C., Subramanian, S., Pal, C. J., Anbil Parthipan, S. C., & Bengio, Y. (juillet 2019). Do neural dialog systems use the conversation history effectively? An empirical study [Communication écrite]. 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019), Florence, Italy. Lien externe

Mémoire ou thèse hors Polytechnique

Anbil Parthipan, S. C. (2019). On challenges in training recurrent neural networks [Thèse de doctorat, Université de Montréal]. Lien externe