Learning Point Processes using Recurrent Graph Network

no code implementations • 11 Aug 2022 • Saurabh Dash, Xueyuan She, Saibal Mukhopadhyay

We present a novel Recurrent Graph Network (RGN) approach for predicting discrete marked event sequences by learning the underlying complex stochastic process.

Graph Attention Point Processes

Unsupervised Hebbian Learning on Point Sets in StarCraft II

no code implementations • 13 Jul 2022 • Beomseok Kang, Harshit Kumar, Saurabh Dash, Saibal Mukhopadhyay

Learning the evolution of real-time strategy (RTS) game is a challenging problem in artificial intelligent (AI) system.

Decoder Self-Supervised Learning +2

Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods

no code implementations • ICLR 2022 • Xueyuan She, Saurabh Dash, Saibal Mukhopadhyay

Moreover, we prove that heterogeneous neurons with varying dynamics and skip-layer connections improve sequence approximation using feedforward SNN.

Gesture Recognition Image Classification +1

Physics-Incorporated Convolutional Recurrent Neural Networks for Source Identification and Forecasting of Dynamical Systems

1 code implementation • 14 Apr 2020 • Priyabrata Saha, Saurabh Dash, Saibal Mukhopadhyay

Spatio-temporal dynamics of physical processes are generally modeled using partial differential equations (PDEs).