5 papers
Probabilistic Prediction of Neural Dynamics via Autoregressive Flow Matching
Nicole Rogalla, Yuzhen Qin, Mario Senden +2
Forecasting neural activity in response to naturalistic stimuli remains a key challenge for understanding brain dynamics and enabling downstream neurotechnological applications. He…
Emergence of Internal State-Modulated Swarming in Multi-Agent Patch Foraging System
Siddharth Chaturvedi, Ahmed EL-Gazzar, Marcel van Gerven
Active particles are entities that sustain persistent out-of-equilibrium motion by consuming energy. Under certain conditions, they exhibit the tendency to self-organize through co…
Role Differentiation in a Coupled Resource Ecology under Multi-Level Selection
Siddharth Chaturvedi, Ahmed El-Gazzar, Marcel van Gerven
A group of non-cooperating agents can succumb to the \emph{tragedy-of-the-commons} if all of them seek to maximize the same resource channel to improve their viability. In nature,…
Probabilistic Forecasting via Autoregressive Flow Matching
Ahmed ElGazzar, Marcel van Gerven
In this work, we propose FlowTime, a generative model for probabilistic forecasting of multivariate timeseries data. Given historical measurements and optional future covariates, w…
ABMax: A JAX-based Agent-based Modeling Framework
Siddharth Chaturvedi, Ahmed El-Gazzar, Marcel van Gerven
Agent-based modeling (ABM) is a principal approach for studying complex systems. By decomposing a system into simpler, interacting agents, agent-based modeling (ABM) allows researc…