Search Results for author:
Found 6 papers, 2 papers with code
Conceptualizing Suicidal Behavior: Utilizing Explanations of Predicted Outcomes to Analyze Longitudinal Social Media Data
The COVID-19 pandemic has escalated mental health crises worldwide, with social isolation and economic instability contributing to a rise in suicidal behavior.
Predicting Short Term Energy Demand in Smart Grid: A Deep Learning Approach for Integrating Renewable Energy Sources in Line with SDGs 7, 9, and 13
However, the intermittent nature of renewable energy sources can make it challenging to manage the power grid and ensure a stable supply of electricity, which is crucial for achieving SDG 9.
DQNAS: Neural Architecture Search using Reinforcement Learning
Convolutional Neural Networks have been used in a variety of image related applications after their rise in popularity due to ImageNet competition.
Constraining the Fast Radio Burst (FRB) properties using the joint distributions of dispersion measure and fluence of the events detected at Parkes, ASKAP, CHIME and UTMOST
Considering the allowed $(\alpha, \E33)$ parameter range, we predict that CHIME is unlikely to detect an FRB with extra-galactic dispersion measure $(DM_{Ex})$ exceeding $3700\,{\rm pc\, cm}^{-3}$.
High Energy Astrophysical Phenomena Cosmology and Nongalactic Astrophysics
Qutrit-inspired Fully Self-supervised Shallow Quantum Learning Network for Brain Tumor Segmentation
Classical self-supervised networks suffer from convergence problems and reduced segmentation accuracy due to forceful termination.
Comparative study of variational quantum circuit and quantum backpropagation multilayer perceptron for COVID-19 outbreak predictions
There are numerous models of quantum neural networks that have been applied to variegated problems such as image classification, pattern recognition etc. Quantum inspired algorithms have been relevant for quite awhile.
