collaborators

11 papers

cs.LG2026

Topology-Aware Gaussian Graph Repair for Robust Graph Neural Networks

Anubha Goel, Juho Kanniainen

Graph neural networks have achieved strong performance on graph-structured data, but their effectiveness depends heavily on the quality of the observed graph. In real applications,…

cs.SI2026

Learning hidden cascades via classification

Derrick Gilchrist Edward Manoharan, Anubha Goel, Alexandros Iosifidis +2

The spreading dynamics in social networks are often studied under the assumption that individuals' statuses, whether informed or infected, are fully observable. However, in many re…

q-fin.PM2026

Class of topological portfolios: Are they better than classical portfolios?

Anubha Goel, Amita Sharma, Juho Kanniainen

Topological Data Analysis (TDA), an emerging field in investment sciences, harnesses mathematical methods to extract data features based on shape, offering a promising alternative…

cs.AI2025

LOBERT: Generative AI Foundation Model for Limit Order Book Messages

Eljas Linna, Kestutis Baltakys, Alexandros Iosifidis +1

Modeling the dynamics of financial Limit Order Books (LOB) at the message level is challenging due to irregular event timing, rapid regime shifts, and the reactions of high-frequen…

q-fin.CP2025

Prospects of Imitating Trading Agents in the Stock Market

Mateusz Wilinski, Juho Kanniainen

In this work we show how generative tools, which were successfully applied to limit order book data, can be utilized for the task of imitating trading agents. To this end, we propo…

q-fin.CP2025

Agent-based model of information diffusion in the limit order book trading

Mateusz Wilinski, Juho Kanniainen

There are multiple explanations for stylized facts in high-frequency trading, including adaptive and informed agents, many of which have been studied through agent-based models. Th…