CHIP: A Hawkes Process Model for Continuous-time Networks with Scalable and Consistent Estimation M Arastuie, S Paul, KS Xu Advances in neural information processing systems 33, 2020 | 24 | 2020 |
IdeasLabUT/dynetworkx: Python package for importing and analyzing discrete-and continuous-time dynamic networks T Hilsabeck, M Arastuie, HN Do, M Sloma, KS Xu URL https://github. com/IdeasLabUT/dynetworkx, 2020 | 3 | 2020 |
Activity recognition by classification with time stabilization for the SHL recognition challenge M Sloma, M Arastuie, KS Xu Proceedings of the 2018 ACM International Joint Conference and 2018 …, 2018 | 3 | 2018 |
A hybrid adjacency and time-based data structure for analysis of temporal networks T Hilsabeck, M Arastuie, KS Xu Applied Network Science 7 (1), 44, 2022 | 1 | 2022 |
Personalized degrees: Effects on link formation in dynamic networks from an egocentric perspective M Arastuie, K S. Xu Companion Proceedings of The 2019 World Wide Web Conference, 1039-1046, 2019 | 1 | 2019 |
Generative Models of Link Formation and Community Detection in Continuous-Time Dynamic Networks M Arastuie The University of Toledo, 2020 | | 2020 |