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09/01/2023
Geometry-aware Line Graph Transformer Pre-training for Molecular Property Prediction
Molecular property prediction with deep learning has gained much attenti...
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05/09/2023
SkelEx and BoundEx: Natural Visualization of ReLU Neural Networks
Despite their limited interpretability, weights and biases are still the...
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03/14/2023
Tensor-based Multimodal Learning for Prediction of Pulmonary Arterial Wedge Pressure from Cardiac MRI
Heart failure is a serious and life-threatening condition that can lead ...
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11/29/2022
Multimodal Learning for Multi-Omics: A Survey
With advanced imaging, sequencing, and profiling technologies, multiple ...
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08/03/2022
Interpretable bilinear attention network with domain adaptation improves drug-target prediction
Predicting drug-target interaction is key for drug discovery. Recent dee...
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06/27/2022
Knowledge-aware Neural Collective Matrix Factorization for Cross-domain Recommendation
Cross-domain recommendation (CDR) can help customers find more satisfyin...
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03/04/2022
Uncertainty Estimation for Heatmap-based Landmark Localization
Automatic anatomical landmark localization has made great strides by lev...
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11/18/2021
Evaluating Transformers for Lightweight Action Recognition
In video action recognition, transformers consistently reach state-of-th...
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08/17/2021
Channel-Temporal Attention for First-Person Video Domain Adaptation
Unsupervised Domain Adaptation (UDA) can transfer knowledge from labeled...
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07/01/2021
VideoLightFormer: Lightweight Action Recognition using Transformers
Efficient video action recognition remains a challenging problem. One la...
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06/22/2021
Team PyKale (xy9) Submission to the EPIC-Kitchens 2021 Unsupervised Domain Adaptation Challenge for Action Recognition
This report describes the technical details of our submission to the EPI...
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06/17/2021
PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python
Machine learning is a general-purpose technology holding promises for ma...
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12/21/2020
Unifying Homophily and Heterophily Network Transformation via Motifs
Higher-order proximity (HOP) is fundamental for most network embedding m...
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12/21/2020
Hop-Hop Relation-aware Graph Neural Networks
Graph Neural Networks (GNNs) are widely used in graph representation lea...
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10/29/2020
GripNet: Graph Information Propagation on Supergraph for Heterogeneous Graphs
Heterogeneous graph representation learning aims to learn low-dimensiona...
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01/28/2020
Tri-graph Information Propagation for Polypharmacy Side Effect Prediction
The use of drug combinations often leads to polypharmacy side effects (P...
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03/26/2019
Domain Independent SVM for Transfer Learning in Brain Decoding
Brain imaging data are important in brain sciences yet expensive to obta...
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12/25/2018
Mixed-Order Spectral Clustering for Networks
Clustering is fundamental for gaining insights from complex networks, an...
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12/04/2018
Sturm: Sparse Tubal-Regularized Multilinear Regression for fMRI
While functional magnetic resonance imaging (fMRI) is important for heal...
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11/30/2018
Graph Node-Feature Convolution for Representation Learning
Graph convolutional network (GCN) is an emerging neural network approach...
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04/30/2015