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DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents

Scalability and accuracy are well recognized challenges in deep extreme multi-label learning where the objective is to train architectures for automatically annotating a data point with the most relev...

Evaluation of Deep Learning Models for Multi-Step Ahead Time Series Prediction

Time series prediction with neural networks has been the focus of much research in the past few decades. Given the recent deep learning revolution, there has been much attention in using deep learning...

Smooth Maximum Unit: Smooth Activation Function for Deep Networks using Smoothing Maximum Technique

Deep learning researchers have a keen interest in proposing new novel activation functions that can boost neural network performance. A good choice of activation function can have a significant effect...

Predicting lake water quality index with sensitivity-uncertainty analysis using deep learning algorithms

Learning the stress-strain fields in digital composites using Fourier neural operator

Increased demands for high-performance materials have led to advanced composite materials with complex hierarchical designs. However, designing a tailored material microstructure with targeted propert...

Deep learning model for predicting tunnel damages and track serviceability under seismic environment

Influence maximization in social networks using transfer learning via graph-based LSTM

How to Maximize Clicks for Display Advertisement in Digital Marketing? A Reinforcement Learning Approach

COVID-19 image classification using deep learning: Advances, challenges and opportunities

The exploitation of host autophagy and ubiquitin machinery by Mycobacterium tuberculosis in shaping immune responses and host defense during infection

Intracellular pathogens have evolved various efficient molecular armaments to subvert innate defenses. Cellular ubiquitination, a normal physiological process to maintain homeostasis, is emerging one ...

Twin actor twin delayed deep deterministic policy gradient (TATD3) learning for batch process control

Deep Learning Model Based CO2 Emissions Prediction Using Vehicle Telematics Sensors Data

Climate change is one of the greatest environmental hazards to mankind. The emission of greenhouse gases has resulted in a continuous increase in the temperature of the atmosphere leading to Global wa...

Deep learning assisted multi-omics integration for survival and drug-response prediction in breast cancer

BACKGROUND: Survival and drug response are two highly emphasized clinical outcomes in cancer research that directs the prognosis of a cancer patient. Here, we have proposed a late multi omics integrat...

Convolutional neural network based bearing fault diagnosis of rotating machine using thermal images

Identification of disease using deep learning and evaluation of bacteriosis in peach leaf