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Lingxiao Zhao
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2020 – today
- 2024
- [j14]Siddhartha Chib, Lingxiao Zhao
, Guofu Zhou
Winners from Winners: A Tale of Risk Factors. Manag. Sci. 70(1): 396-414 (2024) - [c23]Sathish Reddy Indurthi, Wenxuan Zhou, Shamil Chollampatt, Ravi Agrawal, Kaiqiang Song, Lingxiao Zhao, Chenguang Zhu:
Improving Multilingual Instruction Finetuning via Linguistically Natural and Diverse Datasets. EMNLP (Findings) 2024: 2306-2323 - [c22]Bohang Zhang, Lingxiao Zhao, Haggai Maron:
On the Expressive Power of Spectral Invariant Graph Neural Networks. ICML 2024 - [c21]Meng-Chieh Lee
Descriptive Kernel Convolution Network with Improved Random Walk Kernel. WWW 2024: 457-468 - [i22]Lingxiao Zhao, Xueying Ding, Leman Akoglu:
Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation. CoRR abs/2402.03687 (2024) - [i21]Lingxiao Zhao, Xueying Ding, Lijun Yu
Improving and Unifying Discrete&Continuous-time Discrete Denoising Diffusion. CoRR abs/2402.03701 (2024) - [i20]Meng-Chieh Lee, Lingxiao Zhao, Leman Akoglu:
Descriptive Kernel Convolution Network with Improved Random Walk Kernel. CoRR abs/2402.06087 (2024) - [i19]Bohang Zhang, Lingxiao Zhao, Haggai Maron:
On the Expressive Power of Spectral Invariant Graph Neural Networks. CoRR abs/2406.04336 (2024) - [i18]Sathish Reddy Indurthi, Wenxuan Zhou, Shamil Chollampatt, Ravi Agrawal, Kaiqiang Song, Lingxiao Zhao, Chenguang Zhu:
Improving Multilingual Instruction Finetuning via Linguistically Natural and Diverse Datasets. CoRR abs/2407.01853 (2024) - 2023
- [j13]Lingxiao Zhao
On Using Classification Datasets to Evaluate Graph Outlier Detection: Peculiar Observations and New Insights. Big Data 11(3): 151-180 (2023) - [j12]Jiong Zhu, Yujun Yan, Mark Heimann, Lingxiao Zhao, Leman Akoglu, Danai Koutra:
Heterophily and Graph Neural Networks: Past, Present and Future. IEEE Data Eng. Bull. 46(2): 12-34 (2023) - [j11]Lingxiao Zhao, Saurabh Sawlani, Leman Akoglu:
Density of states for fast embedding node-attributed graphs. Knowl. Inf. Syst. 65(6): 2455-2483 (2023) - [j10]Jinming Wang, Qigang Long, Yan Liang, Jie Song, Yadong Feng
AI-assisted identification of intrapapillary capillary loops in magnification endoscopy for diagnosing early-stage esophageal squamous cell carcinoma: a preliminary study. Medical Biol. Eng. Comput. 61(7): 1631-1648 (2023) - [j9]Lingxiao Zhao
A novel cryptocurrency price time series hybrid prediction model via machine learning with MATLAB/Simulink. J. Supercomput. 79(14): 15358-15389 (2023) - [j8]Haojie Cheng
Fast and Accurate Illumination Estimation Using LDR Panoramic Images for Realistic Rendering. IEEE Trans. Vis. Comput. Graph. 29(12): 5235-5249 (2023) - [c20]Konstantinos Sotiropoulos, Lingxiao Zhao, Pierre Jinghong Liang
ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network Approach. IEEE Big Data 2023: 865-874 - [c19]Lingxiao Zhao
Liquidity and Solvency Risks in Financial Networks. ICAIF 2023: 210-218 - [c18]Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka:
Sign and Basis Invariant Networks for Spectral Graph Representation Learning. ICLR 2023 - [c17]Haojie Cheng, Chunxiao Xu, Xujing Chen, Zhenxin Chen, Jiajun Wang, Lingxiao Zhao:
Realistic Volume Rendering with Environment-Synced Illumination in Mixed Reality. ISMAR-Adjunct 2023: 423-428 - [c16]Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu:
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. ECML/PKDD (1) 2023: 254-269 - [c15]Haojie Cheng, Chunxiao Xu, Zhenxin Chen, Jiajun Wang, Yibo Chen, Lingxiao Zhao:
A Mixed Reality Framework for Interactive Realistic Volume Rendering with Dynamic Environment Illumination. VR Workshops 2023: 741-742 - [i17]Jaemin Yoo, Lingxiao Zhao, Leman Akoglu:
End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection. CoRR abs/2306.12033 (2023) - [i16]Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu:
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. CoRR abs/2307.06534 (2023) - [i15]Haojie Cheng, Chunxiao Xu, Xujing Chen, Zhenxin Chen, Jiajun Wang, Lingxiao Zhao:
Realistic Volume Rendering with Environment-Synced Illumination in Mixed Reality. CoRR abs/2309.01916 (2023) - [i14]Konstantinos Sotiropoulos, Lingxiao Zhao, Pierre Jinghong Liang
ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network Approach. CoRR abs/2311.07355 (2023) - 2022
- [j7]Xin Ma
A dual-branch hybrid dilated CNN model for the AI-assisted segmentation of meningiomas in MR images. Comput. Biol. Medicine 151(Part): 106279 (2022) - [j6]Haojie Cheng
Quad-fisheye Image Stitching for Monoscopic Panorama Reconstruction. Comput. Graph. Forum 41(6): 94-109 (2022) - [c14]Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah:
Graph Condensation for Graph Neural Networks. ICLR 2022 - [c13]Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah:
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. ICLR 2022 - [c12]Xueying Ding, Lingxiao Zhao, Leman Akoglu:
Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution. NeurIPS 2022 - [c11]Lingxiao Zhao, Neil Shah, Leman Akoglu:
A Practical, Progressively-Expressive GNN. NeurIPS 2022 - [i13]Derek Lim, Joshua Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka:
Sign and Basis Invariant Networks for Spectral Graph Representation Learning. CoRR abs/2202.13013 (2022) - [i12]Xueying Ding
Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution. CoRR abs/2206.07647 (2022) - [i11]Lingxiao Zhao, Louis Härtel, Neil Shah, Leman Akoglu:
A Practical, Progressively-Expressive GNN. CoRR abs/2210.09521 (2022) - [i10]Lingxiao Zhao, Saurabh Sawlani, Arvind Srinivasan, Leman Akoglu:
Graph Anomaly Detection with Unsupervised GNNs. CoRR abs/2210.09535 (2022) - 2021
- [j5]Siheng Chen
Graph Unrolling Networks: Interpretable Neural Networks for Graph Signal Denoising. IEEE Trans. Signal Process. 69: 3699-3713 (2021) - [c10]Saurabh Sawlani, Lingxiao Zhao, Leman Akoglu:
Fast Attributed Graph Embedding via Density of States. ICDM 2021: 559-568 - [i9]Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah:
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. CoRR abs/2110.03753 (2021) - [i8]Saurabh Sawlani, Lingxiao Zhao, Leman Akoglu:
Fast Attributed Graph Embedding via Density of States. CoRR abs/2110.05228 (2021) - [i7]Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah:
Graph Condensation for Graph Neural Networks. CoRR abs/2110.07580 (2021) - 2020
- [c9]Lingxiao Zhao, Leman Akoglu:
PairNorm: Tackling Oversmoothing in GNNs. ICLR 2020 - [c8]Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra:
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs. NeurIPS 2020 - [i6]Siheng Chen, Yonina C. Eldar, Lingxiao Zhao:
Graph Unrolling Networks: Interpretable Neural Networks for Graph Signal Denoising. CoRR abs/2006.01301 (2020) - [i5]Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra:
Generalizing Graph Neural Networks Beyond Homophily. CoRR abs/2006.11468 (2020) - [i4]Lingxiao Zhao, Leman Akoglu:
Connecting Graph Convolutional Networks and Graph-Regularized PCA. CoRR abs/2006.12294 (2020) - [i3]Lingxiao Zhao, Leman Akoglu:
On Using Classification Datasets to Evaluate Graph Outlier Detection: Peculiar Observations and New Insights. CoRR abs/2012.12931 (2020)
2010 – 2019
- 2019
- [j4]Lei Wang, Yibo Chen, Zhenying Zhao, Lingxiao Zhao, Jin Li, Cuimin Li:
A multi-modal health data fusion and analysis method based on body sensor network. Int. J. Serv. Technol. Manag. 25(5/6): 474-491 (2019) - [i2]Lingxiao Zhao, Leman Akoglu:
PairNorm: Tackling Oversmoothing in GNNs. CoRR abs/1909.12223 (2019) - [i1]Xuan Wu, Lingxiao Zhao, Leman Akoglu:
A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification. CoRR abs/1909.12385 (2019) - 2018
- [c7]Lei Wang, Wei Sun, Yibo Chen, Peng Li, Lingxiao Zhao:
Multimode Data Fusion Based Remote Healthcare Framework. BDET 2018: 1-6 - [c6]Xuan Wu, Lingxiao Zhao, Leman Akoglu:
A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification. CIKM 2018: 87-96 - [c5]Lingxiao Zhao, Shuangzhi Li, Jiankang Zhang, Xiaomin Mu:
A Parafac-Based Blind Channel Estimation and Symbol Detection Scheme for Massive MIMO Systems. CyberC 2018 - [c4]Lei Wang, Wei Sun, Yibo Chen, Peng Li, Lingxiao Zhao:
Wavelet Transform Based ECG Denoising Using Adaptive Thresholding. ICBBS 2018: 35-40
2000 – 2009
- 2009
- [j3]Lingxiao Zhao, Zhenyue Zhang:
Supervised locally linear embedding with probability-based distance for classification. Comput. Math. Appl. 57(6): 919-926 (2009) - [c3]Vincent Frans van Ravesteijn, Lingxiao Zhao, Charl P. Botha, Frits H. Post, Frans M. Vos, Lucas J. van Vliet
Combining Mesh, Volume, and Streamline Representations for Polyp Detection in CT Colonography. ISBI 2009: 907-910 - 2008
- [c2]Lingxiao Zhao, Vincent Frans van Ravesteijn, Charl P. Botha, Roel Truyen, Frans M. Vos, Frits H. Post:
Surface Curvature Line Clustering for Polyp Detection in CT Colonography. VCBM 2008: 53-60 - 2007
- [j2]Xiaozhe Hu, Lingxiao Zhao, Abdul Wasim Shaikh:
The boundary penalty method for the diffusion equation subject to the specification of mass. Appl. Math. Comput. 186(1): 735-748 (2007) - [c1]Zhenyue Zhang, Lingxiao Zhao:
Probability-Based Locally Linear Embedding for Classification. FSKD (3) 2007: 243-247 - [p1]Robert S. Laramee
Topology-Based Flow Visualization, The State of the Art. Topology-based Methods in Visualization 2007: 1-19 - 2006
- [j1]Lingxiao Zhao, Charl P. Botha, Javier Oliván Bescós, Roel Truyen, Frans Vos, Frits H. Post:
Lines of Curvature for Polyp Detection in Virtual Colonoscopy. IEEE Trans. Vis. Comput. Graph. 12(5): 885-892 (2006)
Coauthor Index
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last updated on 2024-11-19 20:44 CET by the dblp team
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