Learning on graphs is becoming prevalent in a wide range of applications...
The tropical cyclone formation process is one of the most complex natura...
In peer-to-peer (P2P) energy trading, a secured infrastructure is requir...
The present work proposes analytical solutions for the integral of bivar...
Graph neural network (GNN) is achieving remarkable performances in a var...
This paper presents a parallel implementation for the Optimal
Transporta...
Trusted execution environments (TEEs) such as facilitate the secure
exec...
Deep learning researchers have a keen interest in proposing two new nove...
Well-known activation functions like ReLU or Leaky ReLU are
non-differen...
An activation function is a crucial component of a neural network that
i...
Tropical cyclones are one of the most powerful and destructive natural
p...
Tropical cyclones can be of varied intensity and cause a huge loss of li...
The prediction of the intensity, location and time of the landfall of a
...
Landfall of a tropical cyclone is the event when it moves over the land ...
Modern enterprise servers are increasingly embracing tiered memory syste...
In this work, we propose a mathematical model for a physical problem bas...
The main purpose is to describe the evolution of = ∧_- ,
with (s,0) a re...
Activation functions play a pivotal role in the function learning using
...
Deep learning at its core, contains functions that are composition of a
...
The aim of this article is twofold. First, we show the evolution of the
...
In the last 150 years, CO2 concentration in the atmosphere has increased...
Generating natural questions from an image is a semantic task that requi...
This paper considers the problem of robustly estimating the parameters o...
Learning a graph with a specific structure is essential for interpretabi...
In this paper a variant of the Hill cipher is proposed. In the classical...
In this paper, we consider the evolution of the Vortex Filament equation...
Data centers have become center of big data processing. Most programs ru...
In this two-part work, we propose an algorithmic framework for solving
n...
Graph learning from data represents a canonical problem that has receive...
In this work, an integrated performance evaluation of a decode-and-forwa...
The autoregressive (AR) model is a widely used model to understand time
...
Generating natural questions from an image is a semantic task that requi...
In this paper, we propose a method for obtaining sentence-level embeddin...
CPU Scheduling is the base of multiprogramming. Scheduling is a process ...
Multidimensional scaling (MDS) is a popular dimensionality reduction
tec...
Artificial Bee Colony (ABC) optimization algorithm is one of the recent
...
Differential Evolution (DE) is a renowned optimization stratagem that ca...
Artificial Bee Colony (ABC) is a distinguished optimization strategy tha...
Artificial bee colony (ABC) algorithm has proved its importance in solvi...