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