Search Results for author: Yixuan He

Found 12 papers, 10 papers with code

Robust Angular Synchronization via Directed Graph Neural Networks

no code implementations9 Oct 2023 Yixuan He, Gesine Reinert, David Wipf, Mihai Cucuringu

The angular synchronization problem aims to accurately estimate (up to a constant additive phase) a set of unknown angles $\theta_1, \dots, \theta_n\in[0, 2\pi)$ from $m$ noisy measurements of their offsets $\theta_i-\theta_j \;\mbox{mod} \; 2\pi.$ Applications include, for example, sensor network localization, phase retrieval, and distributed clock synchronization.


DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion

1 code implementation23 Jan 2023 Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan

Real-world data generation often involves complex inter-dependencies among instances, violating the IID-data hypothesis of standard learning paradigms and posing a challenge for uncovering the geometric structures for learning desired instance representations.

Image-text Classification Node Classification +2

MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian

1 code implementation1 Sep 2022 Yixuan He, Michael Permultter, Gesine Reinert, Mihai Cucuringu

In these experiments, we consider tasks related to signed information, tasks related to directional information, and tasks related to both signed and directional information.

Link Prediction Node Clustering +3

CEP3: Community Event Prediction with Neural Point Process on Graph

no code implementations21 May 2022 Xuhong Wang, Sirui Chen, Yixuan He, Minjie Wang, Quan Gan, Yupu Yang, Junchi Yan

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 represented as an edge along with its occurrence timestamp in the graphs. However, most previous works approach the problem in compromised settings, either formulating it as a link prediction task on the graph given the event time or a time prediction problem given which event will happen next.

Link Prediction

PyTorch Geometric Signed Directed: A Software Package on Graph Neural Networks for Signed and Directed Graphs

1 code implementation22 Feb 2022 Yixuan He, Xitong Zhang, JunJie Huang, Benedek Rozemberczki, Mihai Cucuringu, Gesine Reinert

While many networks are signed or directed, or both, there is a lack of unified software packages on graph neural networks (GNNs) specially designed for signed and directed networks.

Time Series Time Series Analysis

GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks

1 code implementation1 Feb 2022 Yixuan He, Quan Gan, David Wipf, Gesine Reinert, Junchi Yan, Mihai Cucuringu

In this paper, we introduce neural networks into the ranking recovery problem by proposing the so-called GNNRank, a trainable GNN-based framework with digraph embedding.

Inductive Bias

SSSNET: Semi-Supervised Signed Network Clustering

1 code implementation13 Oct 2021 Yixuan He, Gesine Reinert, Songchao Wang, Mihai Cucuringu

Node embeddings are a powerful tool in the analysis of networks; yet, their full potential for the important task of node clustering has not been fully exploited.

Cloud Removal Clustering +3

DIGRAC: Digraph Clustering Based on Flow Imbalance

1 code implementation9 Jun 2021 Yixuan He, Gesine Reinert, Mihai Cucuringu

DIGRAC optimizes directed flow imbalance for clustering without requiring label supervision, unlike existing graph neural network methods, and can naturally incorporate node features, unlike existing spectral methods.

Clustering Graph Clustering +1

MagNet: A Neural Network for Directed Graphs

1 code implementation NeurIPS 2021 Xitong Zhang, Yixuan He, Nathan Brugnone, Michael Perlmutter, Matthew Hirn

In this paper, we propose MagNet, a spectral GNN for directed graphs based on a complex Hermitian matrix known as the magnetic Laplacian.

Link Prediction Node Classification

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

1 code implementation8 Jun 2019 Yixuan He, Tianyi Hu, Delu Zeng

Experimental results show that the proposed algorithm can generate precise masks that allow for various machine learning tasks such as supervised training.


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

1 code implementation15 May 2018 Delu Zeng, Yixuan He, Li Liu, Zhihong Chen, Jiabin Huang, Jie Chen, John Paisley

In this paper, we propose an end-to-end generic salient object segmentation model called Metric Expression Network (MEnet) to deal with saliency detection with the tolerance of distortion.

Saliency Detection Semantic Segmentation

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