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10/04/2022
Multiple Instance Learning for Detecting Anomalies over Sequential Real-World Datasets
Detecting anomalies over real-world datasets remains a challenging task....
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10/01/2022
Multi-objective Deep Data Generation with Correlated Property Control
Developing deep generative models has been an emerging field due to the ...
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06/17/2022
Transformer Neural Networks Attending to Both Sequence and Structure for Protein Prediction Tasks
The increasing number of protein sequences decoded from genomes is openi...
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02/28/2022
Interpretable Molecular Graph Generation via Monotonic Constraints
Designing molecules with specific properties is a long-lasting research ...
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10/04/2021
Traffic Flow Forecasting with Maintenance Downtime via Multi-Channel Attention-Based Spatio-Temporal Graph Convolutional Networks
Forecasting traffic flows is a central task in intelligent transportatio...
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04/20/2021
Space Partitioning and Regression Mode Seeking via a Mean-Shift-Inspired Algorithm
The mean shift (MS) algorithm is a nonparametric method used to cluster ...
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10/03/2020
Decoy Selection for Protein Structure Prediction Via Extreme Gradient Boosting and Ranking
Identifying one or more biologically-active/native decoys from millions ...
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06/09/2020
Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement
Disentangled representation learning has recently attracted a significan...
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04/08/2020
Generating Tertiary Protein Structures via an Interpretative Variational Autoencoder
Much scientific enquiry across disciplines is founded upon a mechanistic...
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05/20/2019