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Causality-driven feature representation for connectivity prediction [PDF]

Frontiers in Artificial Intelligence
Causal reasoning is essential for understanding relationships and guiding decision-making in different applications, as it allows for the identification of cause-and-effect relationships between variables. By uncovering the underlying process that drives
Bruno Souza, Manuel Castro, Ahmed Esmin, Ahmed Esmin, Leonardo Machado, Alexandre Ferreira, Anderson Rocha   +6 more
doaj   +2 more sources

Auto-Encoding Generative Adversarial Networks towards Mode Collapse Reduction and Feature Representation Enhancement [PDF]

Entropy, 2023
Generative Adversarial Nets (GANs) are a kind of transformative deep learning framework that has been frequently applied to a large variety of applications related to the processing of images, video, speech, and text.
Yang Zou, Yuxuan Wang, Xiaoxiang Lu
doaj   +2 more sources

MSDSANet: Multimodal Emotion Recognition Based on Multi-Stream Network and Dual-Scale Attention Network Feature Representation [PDF]

Sensors
Aiming at the shortcomings of EEG emotion recognition models in feature representation granularity and spatiotemporal dependence modeling, a multimodal emotion recognition model integrating multi-scale feature representation and attention mechanism is ...
Weitong Sun, Xingya Yan, Yuping Su, Gaihua Wang, Yumei Zhang   +4 more
doaj   +2 more sources

Successor Feature Representations

Transactions on Machine Learning Research, 2021
published in Transactions on Machine Learning Research (05/2023), source code: https://gitlab.inria.fr/robotlearn/sfr_learning, [v2] added experiments with learned features, [v3] renamed paper and changed scope, [v4] published ...
Reinke, Chris, Alameda-Pineda, Xavier
openaire   +3 more sources

Statistical summary representations of bound features [PDF]

Attention, Perception, & Psychophysics, 2020
The visual system can efficiently summarize various lower-level and higher-level features of ensembles. However, no research to date has directly investigated how different features interact with each other within a single summary and whether people can efficiently report an integrated summary of two feature dimensions. In the first two experiments, we
Boduroglu, Aysecan, Yildirim, Irem
openaire   +3 more sources

A Deep Learning Approach for Robust Detection of Bots in Twitter Using Transformers

IEEE Access, 2021
During the last decades, the volume of multimedia content posted in social networks has grown exponentially and such information is immediately propagated and consumed by a significant number of users.
David Martin-Gutierrez, Gustavo Hernandez-Penaloza, Alberto Belmonte Hernandez, Alicia Lozano-Diez, Federico Alvarez   +4 more
doaj   +1 more source

Prediction of Drug-Drug Interaction Using an Attention-Based Graph Neural Network on Drug Molecular Graphs

Molecules, 2022
The treatment of complex diseases by using multiple drugs has become popular. However, drug-drug interactions (DDI) may give rise to the risk of unanticipated adverse effects and even unknown toxicity.
Yue-Hua Feng, Shao-Wu Zhang
doaj   +1 more source

Guided Random Projection: A Lightweight Feature Representation for Image Classification

IEEE Access, 2021
Modern neural networks [e.g., Deep Neural Networks (DNNs)] have recently gained increasing attention for visible image classification tasks. Their success mainly results from capabilities in learning a complex feature mapping of inputs (i.e., feature ...
Shichao Zhou, Junbo Wang, Wenzheng Wang, Linbo Tang, Baojun Zhao   +4 more
doaj   +1 more source

A Multi-Domain Collaborative Transfer Learning Method with Multi-Scale Repeated Attention Mechanism for Underwater Side-Scan Sonar Image Classification

Remote Sensing, 2022
Due to the strong speckle noise caused by the seabed reverberation which makes it difficult to extract discriminating and noiseless features of a target, recognition and classification of underwater targets using side-scan sonar (SSS) images is a big ...
Zhen Cheng, Guanying Huo, Haisen Li
doaj   +1 more source

Optimization of Discrete Wavelet Transform Feature Representation and Hierarchical Classification of G-Protein Coupled Receptor Using Firefly Algorithm and Particle Swarm Optimization

Applied Sciences, 2022
Ineffective protein feature representation poses problems in protein classification in hierarchical structures. Discrete wavelet transform (DWT) is a feature representation method which generates global and local features based on different wavelet ...
Nor Ashikin Mohamad Kamal, Azuraliza Abu Bakar, Suhaila Zainudin   +2 more
doaj   +1 more source