Search Results for author: Sibo Wang

Found 9 papers, 7 papers with code

Customizable Perturbation Synthesis for Robust SLAM Benchmarking

1 code implementation12 Feb 2024 Xiaohao Xu, Tianyi Zhang, Sibo Wang, Xiang Li, Yongqi Chen, Ye Li, Bhiksha Raj, Matthew Johnson-Roberson, Xiaonan Huang

To this end, we propose a novel, customizable pipeline for noisy data synthesis, aimed at assessing the resilience of multi-modal SLAM models against various perturbations.

Benchmarking Simultaneous Localization and Mapping

Inductive Link Prediction for Nodes Having Only Attribute Information

1 code implementation16 Jul 2020 Yu Hao, Xin Cao, Yixiang Fang, Xike Xie, Sibo Wang

In attributed graphs, both the structure and attribute information can be utilized for link prediction.

Attribute Inductive Link Prediction

Deep Learning at Scale for the Construction of Galaxy Catalogs in the Dark Energy Survey

2 code implementations5 Dec 2018 Asad Khan, E. A. Huerta, Sibo Wang, Robert Gruendl, Elise Jennings, Huihuo Zheng

Furthermore, we use our neural network model as a feature extractor for unsupervised clustering and find that unlabeled DES images can be grouped together in two distinct galaxy classes based on their morphology, which provides a heuristic check that the learning is successfully transferred to the classification of unlabelled DES images.

Clustering

Learning Based Proximity Matrix Factorization for Node Embedding

1 code implementation10 Jun 2021 Xingyi Zhang, Kun Xie, Sibo Wang, Zengfeng Huang

Recent progress on node embedding shows that proximity matrix factorization methods gain superb performance and scale to large graphs with millions of nodes.

Link Prediction Node Classification

Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection

1 code implementation4 Oct 2023 Xiangyu Dong, Xingyi Zhang, Sibo Wang

Moreover, we prove that the accumulated spectral energy of the graph signal can be represented by its Rayleigh Quotient, indicating that the Rayleigh Quotient is a driving factor behind the anomalous properties of graphs.

Anomaly Detection

Instant Graph Neural Networks for Dynamic Graphs

no code implementations3 Jun 2022 Yanping Zheng, Hanzhi Wang, Zhewei Wei, Jiajun Liu, Sibo Wang

With the development of numerous GNN variants, recent years have witnessed groundbreaking results in improving the scalability of GNNs to work on static graphs with millions of nodes.

Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial Robustness

no code implementations9 Jan 2024 Sibo Wang, Jie Zhang, Zheng Yuan, Shiguang Shan

Large-scale pre-trained vision-language models like CLIP have demonstrated impressive performance across various tasks, and exhibit remarkable zero-shot generalization capability, while they are also vulnerable to imperceptible adversarial examples.

Adversarial Robustness Zero-shot Generalization

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