Search results
Results: 15
Number of items: 15
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Provatorova, V., Vakulenko, S., Bhargav, S., & Kanoulas, E. (2021, August 13). ShadowLink [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5196175
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Bhargav, S., & Kanoulas, E. (2021). Controllable Recommenders using Deep Generative Models and Disentanglement. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2110.05056 -
Provatorova, V., Bhargav, S., Vakulenko, S., & Kanoulas, E. (2021). Robustness Evaluation of Entity Disambiguation Using Prior Probes: the Case of Entity Overshadowing. In M.-C. Moens, X. Huang, L. Specia, & S. W. Yih (Eds.), 2021 Conference on Empirical Methods in Natural Language Processing: EMNLP 2021 : proceedings of the conference : November 7-11, 2021 (pp. 10501-10510). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.emnlp-main.820
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Bhargav, S., van Noord, N., & Kamps, J. (2019). Deep learning as a tool for early cinema analysis. In SUMAC '19: proceedings of the 1st Workshop on Structuring and Understanding of Multimedia Heritage Contents : October 21, 2019, Nice, France (pp. 61-68). The Association for Computing Machinery. https://doi.org/10.1145/3347317.3357240
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Patrini, G., van den Berg, R., Forré, P., Carioni, M., Bhargav, S., Welling, M., Genewein, T., & Nielsen, F. (2019). Sinkhorn AutoEncoders. In A. Globerson, & R. Silva (Eds.), Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence: UAI 2019, Tel Aviv, Israel, July 22-25, 2019 Article 253 AUAI Press. https://arxiv.org/abs/1810.01118
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