Vasiliauskaite, V., & Antulov-Fantulin, N. (2023). How accurate are neural approximations of complex network dynamics? link
Gheorghiade, P., Vasiliauskaite, V., Diachenko, A., Price, H., Evans, T., & Rivers, R. (2023). Entropology: an information-theoretic approach to understanding archaeological data. Journal of Archaeological Method and Theory, 30(4), 1109-1141. link
Vasiliauskaite, V., Hausladen, C.I. (2023). How Do Circadian Rhythms and Neural Synchrony Shape Networked Cooperation? Front. Phys. Sec. Social Physics 11-17 link
M. Eren Akbiyik, Mert Erkul, Killian Kämpf, Vaiva Vasiliauskaite, and Nino Antulov-Fantulin. 2023. Ask “Who”, Not “What”: Bitcoin Volatility Forecasting with Twitter Data. In Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (WSDM ’23), February 27–March 3, 2023, Singapore, Singapore. link
Krishna, V., Vasiliauskaite, V., & Antulov-Fantulin, N. (2022). Question routing via activity-weighted modularity-enhanced factorization. Social Network Analysis and Mining, 12(1), 155. link
Vasiliauskaite, V., Evans, T. S., & Expert, P. (2022). Cycle analysis of Directed Acyclic Graphs. Physica A: Statistical Mechanics and its Applications, 596, 127097. link
Vasiliauskaite, V., Lillo, F., & Antulov-Fantulin, N. (2022). Information dynamics of price and liquidity around the 2017 Bitcoin markets crash. Chaos: An Interdisciplinary Journal of Nonlinear Science, 32(4), 043123. link
Vasiliauskaite, V., Antulov-Fantulin, N., & Helbing, D. (2022). On some fundamental challenges in monitoring epidemics. Philosophical Transactions of the Royal Society A, 380(2214), 20210117. link
Vasiliauskaite, V., & Evans, T. S. (2020). Making communities show respect for order. Applied Network Science, 5(1), 1-24. link
Evans, T. S., Calmon, L., & Vasiliauskaite, V. (2020). The longest path in the Price model. Scientific reports, 10(1), 1-9. link
Vasiliauskaite, V., & Rosas, F. E. (2020). Understanding complexity via network theory: a gentle introduction. arXiv preprint arXiv:2004.14845. link
Vasiliauskaite, V., & Evans, T. S. (2019). Social success of perfumes. PloS one, 14(7), e0218664. link
Vasiliauskaite, V., & Evans, T. S. (2018). Diversity from the topology of citation networks. arXiv preprint arXiv:1802.06015. link
My thesis
Vasiliauskaite, V. (2020). Paths and directed acyclic graphs (Doctoral dissertation, Imperial College London). link
List of invited/conference talks
(Upcoming) The role of generalized directed cycles in information processing – NetSci (Quebec City, Canada, 2024).
(Upcoming) Neural Approximations of Dynamics in Complex Systems – NetSci (Quebec City, Canada, 2024).
(A framework for approximating complex network dynamics with graph neural networks and identifying the limits of model’s generalization – Data Science and Mathematical Modeling Seminar, University of Zürich (Zürich, Switzerland, 2024).
How accurate are neural approximations of complex network dynamics? – NetSciX (Venice, Italy, 2024).
Information dynamics of price and liquidity around the 2017 Bitcoin markets crash – UCL (London, UK, 2022).
Challenges in Monitoring Epidemics – Behavioral Studies Colloquium, ETH Zürich (Zürich, Switzerland, 2021).
Making communities show respect for order – NetSciX (Tokyo, Japan, 2020).
The longest path in Price model – NetSci (Burlington, Vermont, USA, 2019).
Making communities show respect for order – NetSci (Burlington, Vermont, USA, 2019).
Centrality and other orderings of nodes in DAGs – NetSci (Paris, France, 2018).
Network of perfumes – NetSci (Paris, France, 2018).