Author of the publication

GPolS: A Contextual Graph-Based Language Model for Analyzing Parliamentary Debates and Political Cohesion.

, , , and . COLING, page 4847-4859. International Committee on Computational Linguistics, (2020)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

 

Other publications of authors with the same name

GPolS: A Contextual Graph-Based Language Model for Analyzing Parliamentary Debates and Political Cohesion., , , and . COLING, page 4847-4859. International Committee on Computational Linguistics, (2020)TEC: A Time Evolving Contextual Graph Model for Speaker State Analysis in Political Debates., , , and . IJCAI, page 3552-3558. ijcai.org, (2021)Modeling financial uncertainty with multivariate temporal entropy-based curriculums., , , , , and . UAI, volume 161 of Proceedings of Machine Learning Research, page 1671-1681. AUAI Press, (2021)Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading., , , and . WWW, page 11-22. ACM / IW3C2, (2021)Hyperbolic Online Time Stream Modeling., , , , and . SIGIR, page 1682-1686. ACM, (2021)Deep Attentive Learning for Stock Movement Prediction From Social Media Text and Company Correlations., , , and . EMNLP (1), page 8415-8426. Association for Computational Linguistics, (2020)Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting., , , and . ICDM, page 482-491. IEEE, (2020)Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach., , , , and . AAAI, page 497-504. AAAI Press, (2021)Quantitative Day Trading from Natural Language using Reinforcement Learning., , , and . NAACL-HLT, page 4018-4030. Association for Computational Linguistics, (2021)FAST: Financial News and Tweet Based Time Aware Network for Stock Trading., , , and . EACL, page 2164-2175. Association for Computational Linguistics, (2021)