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Found 10 papers, 7 papers with code
PGL at TextGraphs 2020 Shared Task: Explanation Regeneration using Language and Graph Learning Methods
To address this problem, we use a pre-trained language model to recall the top-K relevant explanations for each question.
Shifting More Attention to Breast Lesion Segmentation in Ultrasound Videos
We also devise a localization-based contrastive loss to reduce the lesion location distance between neighboring video frames within the same video and enlarge the location distances between frames from different ultrasound videos.
Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials
These spatial-based HGNNs neglect the utilization of spectral graph convolutions, which are the foundation of Graph Convolutional Networks (GCN) on homogeneous graphs.
Ranked #5 on
Node Property Prediction
on ogbn-mag
Label Information Enhanced Fraud Detection against Low Homophily in Graphs
Then, we combine the group aggregation and the learnable encodings into a Transformer encoder to capture the semantic information.
Layout-aware Webpage Quality Assessment
To assess webpage quality from complex DOM tree data, we propose a graph neural network (GNN) based method that extracts rich layout-aware information that implies webpage quality in an end-to-end manner.
Graph4Rec: A Universal Toolkit with Graph Neural Networks for Recommender Systems
In recent years, owing to the outstanding performance in graph representation learning, graph neural network (GNN) techniques have gained considerable interests in many real-world scenarios, such as recommender systems and social networks.
LiteGEM: Lite Geometry Enhanced Molecular Representation Learning for Quantum Property Prediction
In this report, we (SuperHelix team) present our solution to KDD Cup 2021-PCQM4M-LSC, a large-scale quantum chemistry dataset on predicting HOMO-LUMO gap of molecules.
Multimodal and Contrastive Learning for Click Fraud Detection
In this paper, we propose a Multimodal and Contrastive learning network for Click Fraud detection (MCCF).
Molecular Representation Learning by Leveraging Chemical Information
As graph neural networks have achieved great success in many domains, some studies apply graph neural networks to molecular property prediction and regard each molecule as a graph.
Ranked #6 on
Graph Property Prediction
on ogbg-molhiv
Exploring the many-body dynamics near a conical intersection with trapped Rydberg ions
Conical intersections between electronic potential energy surfaces are paradigmatic for the study of non-adiabatic processes in the excited states of large molecules.
Atomic Physics Quantum Physics
