activity
20182022
most citedScan-flood Fill(SCAFF): an Efficient Automatic Precise Region Filling Algorithm for Complicated Regions

3 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2022

CEP3: Community Event Prediction with Neural Point Process on Graph

Xuhong Wang, Sirui Chen, Yixuan He +4

Many real world applications can be formulated as event forecasting on Continuous Time Dynamic Graphs (CTDGs) where the occurrence of a timed event between two entities is represen…

cs.LG2021

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models

Benedek Rozemberczki, Paul Scherer, Yixuan He +8

We present PyTorch Geometric Temporal a deep learning framework combining state-of-the-art machine learning algorithms for neural spatiotemporal signal processing. The main goal of…

cs.LG2021

MagNet: A Neural Network for Directed Graphs

Xitong Zhang, Yixuan He, Nathan Brugnone +2

The prevalence of graph-based data has spurred the rapid development of graph neural networks (GNNs) and related machine learning algorithms. Yet, despite the many datasets natural…

cs.GR20193 cited

Scan-flood Fill(SCAFF): an Efficient Automatic Precise Region Filling Algorithm for Complicated Regions

Yixuan He, Tianyi Hu, Delu Zeng

Recently, instant level labeling for supervised machine learning requires a considerable number of filled masks. In this paper, we propose an efficient automatic region filling alg…

cs.CV2018

Ro-SOS: Metric Expression Network (MEnet) for Robust Salient Object Segmentation

Delu Zeng, Yixuan He, Li Liu +4

Although deep CNNs have brought significant improvement to image saliency detection, most CNN based models are sensitive to distortion such as compression and noise. In this paper,…