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Augmenting Hyperspectral Image Unmixing Models Using Spatial Correlation, Spectral Variability, And Sparsity
Hyperspectral imaging sensors sample sunlight reflected from different targets on Earth's surface by utilising a series of contiguous narrow spectral channels. The higher spectral resolution of hyperspectral images (HSIs) ...
Leveraging KG Embeddings for Knowledge Graph Question Answering
Knowledge graphs (KG) are multi-relational graphs consisting of entities as nodes and relations
among them as typed edges. The goal of knowledge graph question answering (KGQA) is to
answer natural language queries posed ...
Designing Quality of Service aware Serverless Platforms
Serverless computing is a widely used Cloud computing service offering that provides users with managed runtimes to develop their business logic as functions. It supports eventdriven execution of functions and a powerful ...
Application Service Resilience In Cloud: An End-to-End Perspective
The idea of computing as a utility was realized with the emergence of the cloud computing paradigm. Cloud service providers offer a wide range of services that are delivered over the Internet to cloud service consumers. ...
Learning Multiple Initial Conditions using Physics Informed Neural Networks
Physics-Informed Neural Networks (PINNs) and its variants have emerged as a tool for solving differential equations in the past few years. Although several variants of PINNs have been proposed, the majority of these ...
Lesion Synthesis using Physics-Based Noise Models for Low-Data Medical Imaging Regime applications
Lesion segmentation and their progression prediction in medical imaging relies critically on the availability of manually annotated, heterogeneous large pathological datasets. Acquiring such diverse large datasets is also ...
Semi-analytical solution for eigenvalue problems of lattice models with boundary conditions
Closed-form relations for limiting eigenvalues of an infinite k-periodic spatial lattice
in any number of dimensions d, and its semi-analytical extensions for any given size n
of the lattice with free-free boundary ...
Learning from Limited and Imperfect Data
Deep Neural Networks have demonstrated orders of magnitude improvement in capabilities over the years after AlexNet won the ImageNet challenge in 2012. One of the major reasons for this success is the availability of ...
Sparsification of Reaction-Diffusion Dynamical Systems on Complex Networks
Graph sparsification is an area of interest in computer science and applied mathematics. Spar-
sification of a graph, in general, aims to reduce the number of edges in the network while
preserving specific properties of ...
An arbitrary lagrangian eulerian volume of fluid method for floating body dynamics simulation
The floating body dynamics is treated as a Fluid-Structure Interaction (FSI) problem. A FSI problem is where the forces from the fluid move/deform the interacting structure, and the movement of the structure, in turn, ...