most citedA Review of Modularization Techniques in Artificial Neural Networks

77 citations · 86 across the 5 of their papers we have counts for

collaborators

7 papers

cs.LG2020

Towards a Universal Gating Network for Mixtures of Experts

Chen Wen Kang, Chua Meng Hong, Tomas Maul

The combination and aggregation of knowledge from multiple neural networks can be commonly seen in the form of mixtures of experts. However, such combinations are usually done usin…

cs.LG20195 cited

Data Augmentation by AutoEncoders for Unsupervised Anomaly Detection

Kasra Babaei, ZhiYuan Chen, Tomas Maul

This paper proposes an autoencoder (AE) that is used for improving the performance of once-class classifiers for the purpose of detecting anomalies. Traditional one-class classifie…

cs.LG20191 cited

Reducing Catastrophic Forgetting in Modular Neural Networks by Dynamic Information Balancing

Mohammed Amer, Tomás Maul

Lifelong learning is a very important step toward realizing robust autonomous artificial agents. Neural networks are the main engine of deep learning, which is the current state-of…

cs.LG20193 cited

Detecting Point Outliers Using Prune-based Outlier Factor (PLOF)

Kasra Babaei, ZhiYuan Chen, Tomas Maul

Outlier detection (also known as anomaly detection or deviation detection) is a process of detecting data points in which their patterns deviate significantly from others. It is co…

cs.LG2019

Weight Map Layer for Noise and Adversarial Attack Robustness

Mohammed Amer, Tomás Maul

Convolutional neural networks (CNNs) are known for their good performance and generalization in vision-related tasks and have become state-of-the-art in both application and resear…

cs.LG201977 cited

A Review of Modularization Techniques in Artificial Neural Networks

Mohammed Amer, Tomás Maul

Artificial neural networks (ANNs) have achieved significant success in tackling classical and modern machine learning problems. As learning problems grow in scale and complexity, a…