A comprehensive survey of neural architecture search: Challenges and solutions
Deep learning has made substantial breakthroughs in many fields due to its powerful
automatic representation capabilities. It has been proven that neural architecture design is …
automatic representation capabilities. It has been proven that neural architecture design is …
An attentive survey of attention models
Attention Model has now become an important concept in neural networks that has been
researched within diverse application domains. This survey provides a structured and …
researched within diverse application domains. This survey provides a structured and …
Learning improvement heuristics for solving routing problems
Recent studies in using deep learning (DL) to solve routing problems focus on construction
heuristics, whose solutions are still far from optimality. Improvement heuristics have great …
heuristics, whose solutions are still far from optimality. Improvement heuristics have great …
PFmulDL: a novel strategy enabling multi-class and multi-label protein function annotation by integrating diverse deep learning methods
Bioinformatic annotation of protein function is essential but extremely sophisticated, which
asks for extensive efforts to develop effective prediction method. However, the existing …
asks for extensive efforts to develop effective prediction method. However, the existing …
Acceleration for Deep Reinforcement Learning using Parallel and Distributed Computing: A Survey
Deep reinforcement learning has led to dramatic breakthroughs in the field of artificial
intelligence for the past few years. As the amount of rollout experience data and the size of …
intelligence for the past few years. As the amount of rollout experience data and the size of …
A CNN-BiLSTM model with attention mechanism for earthquake prediction
Earthquakes, as natural phenomena, have consistently caused damage and loss of human
life throughout history. Earthquake prediction is an essential aspect of any society's plans …
life throughout history. Earthquake prediction is an essential aspect of any society's plans …
Time-aware attention-based gated network for credit card fraud detection by extracting transactional behaviors
With the popularity of credit cards worldwide, timely and accurate fraud detection has
become critically important to ensure the safety of their user accounts. Existing models …
become critically important to ensure the safety of their user accounts. Existing models …
Multiple dynamic graph based traffic speed prediction method
Traffic speed prediction is a crucial and challenging task for intelligent transportation
systems. The prediction task can be accomplished via graph neural networks with structured …
systems. The prediction task can be accomplished via graph neural networks with structured …
An attention-based LSTM network for large earthquake prediction
Due to the complexity of earthquakes, predicting their magnitude, timing and location is a
challenging task because earthquakes do not show a specific pattern, which can lead to …
challenging task because earthquakes do not show a specific pattern, which can lead to …
The cascaded forward algorithm for neural network training
Backpropagation (BP) algorithm has played a significant role in the development of deep
learning. However, there exist some limitations associated with this algorithm, such as …
learning. However, there exist some limitations associated with this algorithm, such as …