Asynchronous Event

Asynchronous events, characterized by irregularly timed occurrences, are a central focus in various fields, demanding efficient modeling and analysis techniques. Current research emphasizes developing advanced temporal point processes, such as Hawkes processes and their neural network extensions (e.g., incorporating Transformer and Mamba architectures), to capture complex dependencies and nonlinearities within these event streams. This research is driven by the need to address challenges in diverse applications, including robust video reconstruction from event camera data, secure event-based systems (mitigating backdoor attacks), and accurate prediction of future events in domains like finance and healthcare. Improved modeling of asynchronous events promises significant advancements in these and other areas, leading to more efficient and reliable systems.