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Article
Open AccessEffective interpretable learning for large-scale categorical data
Large scale categorical datasets are ubiquitous in machine learning and the success of most deployed machine learning models rely on how effectively the features are engineered. For large-scale datasets, param...
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Article
Adsorption Characteristics And Mechanism of U(Vi) In Water By Dopamine Hydrochloride Modified Bentonite
In this study, bentonite (B) was modified by hydrochloric acid dopamine (PDA), and the modification was confirmed by XRD, SEM, EDS and thermogravimetric analysis. Hydrochloric acid dopamine modified bentonite ...
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Article
Open AccessImproving neural network’s robustness on tabular data with D-layers
Artificial neural networks ( \({{{\texttt {ANN}}}}\) ANN ) are widely used ma...
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Article
Open AccessInterpretable tabular data generation
Generative adversarial network (GAN) models have been successfully utilized in a wide range of machine learning applications, and tabular data generation domain is not an exception. Notably, some state-of-the-art...
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Chapter and Conference Paper
Leveraging Generative Models for Combating Adversarial Attacks on Tabular Datasets
Artificial Neural Networks (ANN) models – a form of discriminative models – are the workhorse of deep learning research, and have resulted in a remarkable performance on a range of applications on a large variety...
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Article
Experimental study on particle circulation characteristics of external circulating fluidized bed evaporator
In order to solve the particle circulation problem of external circulation fluidized bed evaporator, a new particle circulation device was developed, and a cold experiment device was set up for reference to th...
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Chapter and Conference Paper
GUNet: A GCN-CNN Hybrid Model for Retinal Vessel Segmentation by Learning Graphical Structures
In the retinal vessel segmentation task, maintaining graphical structures of vessels is important for the following analysis steps. However, this task is challenging due to the tiny structures of vessels and b...
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Chapter and Conference Paper
Discretization Inspired Defence Algorithm Against Adversarial Attacks on Tabular Data
Deep learning methods are usually trained via a gradient-descent based procedure, which can be efficient as it is not only end-to-end but also suitable for large quantities of data. However, gradient-based lea...
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Chapter and Conference Paper
Predicting User Influence in the Propagation of Toxic Information
With the advances of information technology, the Internet has become an indispensable part of life. At the same time, toxic Information has become virulent and common on the Internet. Such information propagat...
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Chapter and Conference Paper
Topological Graph Representation Learning on Property Graph
Property graph representation learning is using the property features from the graph to build the embeddings over the nodes and edges. There are many graph application tasks are using the property graph repres...
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Chapter and Conference Paper
Duo Attention with Deep Learning on Tomato Yield Prediction and Factor Interpretation
Although many smart farming related approaches have been proposed to support farmers, crop modeling in smart farming and most effective factors for the yield remains an open problem. In this paper, we introduc...
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Chapter and Conference Paper
Deep Supervision with Additional Labels for Retinal Vessel Segmentation Task
Automatic analysis of retinal fundus images is of vital importance in diagnosis tasks of retinopathy. Segmenting vessels accurately is a fundamental step in analysing retinal images. However, it is usually dif...
