Search Results for author: Jianlong Zhou

Found 12 papers, 1 papers with code

ACGAN-GNNExplainer: Auxiliary Conditional Generative Explainer for Graph Neural Networks

no code implementations29 Sep 2023 Yiqiao Li, Jianlong Zhou, Yifei Dong, Niusha Shafiabady, Fang Chen

Graph neural networks (GNNs) have proven their efficacy in a variety of real-world applications, but their underlying mechanisms remain a mystery.

Decision Making Generative Adversarial Network

Ethical ChatGPT: Concerns, Challenges, and Commandments

no code implementations18 May 2023 Jianlong Zhou, Heimo Müller, Andreas Holzinger, Fang Chen

Large language models, e. g. ChatGPT are currently contributing enormously to make artificial intelligence even more popular, especially among the general population.

Chatbot

Explaining Imitation Learning through Frames

no code implementations3 Jan 2023 Boyuan Zheng, Jianlong Zhou, Chunjie Liu, Yiqiao Li, Fang Chen

As one of the prevalent methods to achieve automation systems, Imitation Learning (IL) presents a promising performance in a wide range of domains.

Explainable artificial intelligence Imitation Learning

Genetic Imitation Learning by Reward Extrapolation

no code implementations3 Jan 2023 Boyuan Zheng, Jianlong Zhou, Fang Chen

Imitation learning demonstrates remarkable performance in various domains.

Imitation Learning

GANExplainer: GAN-based Graph Neural Networks Explainer

no code implementations30 Dec 2022 Yiqiao Li, Jianlong Zhou, Boyuan Zheng, Fang Chen

With the rapid deployment of graph neural networks (GNNs) based techniques into a wide range of applications such as link prediction, node classification, and graph classification the explainability of GNNs has become an indispensable component for predictive and trustworthy decision-making.

Decision Making Generative Adversarial Network +3

A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation Metrics

no code implementations26 Jul 2022 Yiqiao Li, Jianlong Zhou, Sunny Verma, Fang Chen

Graph neural networks (GNNs) have demonstrated a significant boost in prediction performance on graph data.

Imitation Learning: Progress, Taxonomies and Challenges

no code implementations23 Jun 2021 Boyuan Zheng, Sunny Verma, Jianlong Zhou, Ivor Tsang, Fang Chen

Imitation learning aims to extract knowledge from human experts' demonstrations or artificially created agents in order to replicate their behaviors.

Autonomous Driving Imitation Learning

Facilitating Machine Learning Model Comparison and Explanation Through A Radial Visualisation

no code implementations15 Apr 2021 Jianlong Zhou, Weidong Huang, Fang Chen

The dependence of ML models with dynamic number of features is encoded into the structure of visualisation, where ML models and their dependent features are directly revealed from related line connections.

BIG-bench Machine Learning Feature Importance

Examination of Community Sentiment Dynamics due to COVID-19 Pandemic: A Case Study from A State in Australia

no code implementations22 Jun 2020 Jianlong Zhou, Shuiqiao Yang, Chun Xiao, Fang Chen

In this paper, we exploit the massive text data posted by Twitter users to analyse the sentiment dynamics of people living in the state of New South Wales (NSW) in Australia during the pandemic period.

Sentiment Analysis

Visual Analytics of Movement Pattern Based on Time-Spatial Data: A Neural Net Approach

no code implementations9 Jul 2017 Zhenghao Chen, Jianlong Zhou, Xiuying Wang

This method aggregates three main parts that are Back-end Data Model, Neural Net Algorithm including clustering method Self-Organizing Map (SOM) and prediction approach Recurrent Neural Net (RNN) for ex- tracting the features and lastly a solid front-end that displays the results to users with an interactive system.

Clustering Management +1

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