4 citations · 17 across the 7 of their papers we have counts for
9 papers
Using Decision Tree as Local Interpretable Model in Autoencoder-based LIME
Niloofar Ranjbar, Reza Safabakhsh
Nowadays, deep neural networks are being used in many domains because of their high accuracy results. However, they are considered as "black box", means that they are not explainab…
Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks
Amirhossein Nouranizadeh, Mohammadjavad Matinkia, Mohammad Rahmati +1
In this paper, we propose a novel pooling layer for graph neural networks based on maximizing the mutual information between the pooled graph and the input graph. Since the maximum…
A Reinforcement Learning Based Encoder-Decoder Framework for Learning Stock Trading Rules
Mehran Taghian, Ahmad Asadi, Reza Safabakhsh
A wide variety of deep reinforcement learning (DRL) models have recently been proposed to learn profitable investment strategies. The rules learned by these models outperform the p…
Learning Financial Asset-Specific Trading Rules via Deep Reinforcement Learning
Mehran Taghian, Ahmad Asadi, Reza Safabakhsh
Generating asset-specific trading signals based on the financial conditions of the assets is one of the challenging problems in automated trading. Various asset trading rules are p…
Detecting Fake News with Capsule Neural Networks
Mohammad Hadi Goldani, Saeedeh Momtazi, Reza Safabakhsh
Fake news is dramatically increased in social media in recent years. This has prompted the need for effective fake news detection algorithms. Capsule neural networks have been succ…
A Deep Decoder Structure Based on WordEmbedding Regression for An Encoder-Decoder Based Model for Image Captioning
Ahmad Asadi, Reza Safabakhsh
Generating textual descriptions for images has been an attractive problem for the computer vision and natural language processing researchers in recent years. Dozens of models base…