9 papers
FLAMES: A Hybrid Spiking-State Space Model for Adaptive Memory Retention in Event-Based Learning
Biswadeep Chakraborty, Saibal Mukhopadhyay
We propose \textbf{FLAMES (Fast Long-range Adaptive Memory for Event-based Systems)}, a novel hybrid framework integrating structured state-space dynamics with event-driven computa…
Dynamic Graph Structure Estimation for Learning Multivariate Point Process using Spiking Neural Networks
Biswadeep Chakraborty, Hemant Kumawat, Beomseok Kang +1
Modeling and predicting temporal point processes (TPPs) is critical in domains such as neuroscience, epidemiology, finance, and social sciences. We introduce the Spiking Dynamic Gr…
Has the Deep Neural Network learned the Stochastic Process? An Evaluation Viewpoint
Harshit Kumar, Beomseok Kang, Biswadeep Chakraborty +1
This paper presents the first systematic study of evaluating Deep Neural Networks (DNNs) designed to forecast the evolution of stochastic complex systems. We show that traditional…
A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks
Biswadeep Chakraborty, Harshit Kumar, Saibal Mukhopadhyay
Oversmoothing in Graph Neural Networks (GNNs) poses a significant challenge as network depth increases, leading to homogenized node representations and a loss of expressiveness. In…
Online Relational Inference for Evolving Multi-agent Interacting Systems
Beomseok Kang, Priyabrata Saha, Sudarshan Sharma +2
We introduce a novel framework, Online Relational Inference (ORI), designed to efficiently identify hidden interaction graphs in evolving multi-agent interacting systems using stre…
RoboKoop: Efficient Control Conditioned Representations from Visual Input in Robotics using Koopman Operator
Hemant Kumawat, Biswadeep Chakraborty, Saibal Mukhopadhyay
Developing agents that can perform complex control tasks from high-dimensional observations is a core ability of autonomous agents that requires underlying robust task control poli…