2 citations · 7 across the 9 of their papers we have counts for
9 papers
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…
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…
Learning Locally Interacting Discrete Dynamical Systems: Towards Data-Efficient and Scalable Prediction
Beomseok Kang, Harshit Kumar, Minah Lee +2
Locally interacting dynamical systems, such as epidemic spread, rumor propagation through crowd, and forest fire, exhibit complex global dynamics originated from local, relatively…
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN
Biswadeep Chakraborty, Beomseok Kang, Harshit Kumar +1
Recurrent Spiking Neural Networks (RSNNs) have emerged as a computationally efficient and brain-inspired learning model. The design of sparse RSNNs with fewer neurons and synapses…
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…
Unsupervised 3D Object Learning through Neuron Activity aware Plasticity
Beomseok Kang, Biswadeep Chakraborty, Saibal Mukhopadhyay
We present an unsupervised deep learning model for 3D object classification. Conventional Hebbian learning, a well-known unsupervised model, suffers from loss of local features lea…
Forecasting Local Behavior of Self-organizing Many-agent System without Reconstruction
Beomseok Kang, Minah Lee, Harshit Kumar +1
Large multi-agent systems are often driven by locally defined agent interactions, which is referred to as self-organization. Our primary objective is to determine when the propagat…
Forecasting Evolution of Clusters in Game Agents with Hebbian Learning
Beomseok Kang, Saibal Mukhopadhyay
Large multi-agent systems such as real-time strategy games are often driven by collective behavior of agents. For example, in StarCraft II, human players group spatially near agent…
Unsupervised Hebbian Learning on Point Sets in StarCraft II
Beomseok Kang, Harshit Kumar, Saurabh Dash +1
Learning the evolution of real-time strategy (RTS) game is a challenging problem in artificial intelligent (AI) system. In this paper, we present a novel Hebbian learning method to…