5 citations · 7 across the 4 of their papers we have counts for
4 papers
Intriguing Properties of Quantization at Scale
Arash Ahmadian, Saurabh Dash, Hongyu Chen +5
Emergent properties have been widely adopted as a term to describe behavior not present in smaller models but observed in larger models. Recent work suggests that the trade-off inc…
Learning Point Processes using Recurrent Graph Network
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. Using the framework…
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…
Physics-Incorporated Convolutional Recurrent Neural Networks for Source Identification and Forecasting of Dynamical Systems
Priyabrata Saha, Saurabh Dash, Saibal Mukhopadhyay
Spatio-temporal dynamics of physical processes are generally modeled using partial differential equations (PDEs). Though the core dynamics follows some principles of physics, real-…