Rishab Goel
Rishab Goel
Verified email at mila.quebec
Cited by
Cited by
Relational representation learning for dynamic (knowledge) graphs: A survey
SM Kazemi, R Goel, K Jain, I Kobyzev, A Sethi, P Forsyth, P Poupart
arXiv preprint arXiv:1905.11485, 2019
Diachronic embedding for temporal knowledge graph completion
R Goel, SM Kazemi, M Brubaker, P Poupart
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3988-3995, 2020
Data-efficient reinforcement learning with momentum predictive representations
M Schwarzer, A Anand, R Goel, RD Hjelm, A Courville, P Bachman
arXiv preprint arXiv:2007.05929, 2020
Time2vec: Learning a vector representation of time
SM Kazemi, R Goel, S Eghbali, J Ramanan, J Sahota, S Thakur, S Wu, ...
arXiv preprint arXiv:1907.05321, 2019
Out-of-Sample Representation Learning for Knowledge Graphs
M Albooyeh, R Goel, SM Kazemi
Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020
Fast retinomorphic event-driven representations for video gameplay and action recognition
H Chen, W Liu, R Goel, RC Lua, S Mittal, Y Huang, A Veeraraghavan, ...
IEEE Transactions on Computational Imaging 6, 276-290, 2019
System and method for diachronic machine learning architecture
SM Kazemi
US Patent App. 16/875,737, 2020
System and method for time-dependent machine learning architecture
JM Ramanan, J Sahota, S EGHBALI, SM KAZEMI
US Patent App. 16/746,866, 2020
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