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Chao Chen

Here is the complete list of my publications.

For further information, please also refer to my Google Scholar and my DBLP Profile.

Conferences

  • Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen, Yusu Wang: "Cycle Invariant Positional Encoding for Graph Representation Learning", in Learning on Graphs Conference (LoG), 2023 (Oral presentation, paper)

  • Weimin Lyu, Songzhu Zheng, Lu Pang, Haibin Ling, Chao Chen: "Attention-Enhancing Backdoor Attacks Against BERT-based Models", in EMNLP Findings , 2023

  • Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen: "Topology-Aware Uncertainty for Image Segmentation", in the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2023 (acceptance rate 26.1%, paper)

  • Chen Li, Xiaoling Hu, Shahira Abousamra, Chao Chen: "Calibrating Uncertainty for Semi-Supervised Crowd Counting", in International Conference on Computer Vision (ICCV), 2023, (acceptance rate 26.15%, paper)

  • Aishik Konwer, Xiaoling Hu, Joseph Bae, Xuan Xu, Chao Chen, Prateek Prasanna: "Enhancing Modality-Agnostic Representations via Meta-Learning for Brain Tumor Segmentation", in International Conference on Computer Vision (ICCV), 2023, (acceptance rate 26.15%, paper)

  • Shahira Abousamra, Danielle Fassler, Jiachen Yao, Rajarsi R. Gupta, Tahsin Kurc, Luisa Escobar-Hoyos, Dimitris Samaras, Kenneth Shroyer, Joel Saltz, Chao Chen: "Unsupervised Stain Decomposition via Inversion Regulation for Multiplex Immunohistochemistry Images", in Medical Imaging with Deep Learning (MIDL), 2023, (Oral presentation, paper)

  • Shahira Abousamra, Rajarsi Gupta, Tahsin Kurc, Dimitris Samaras, Joel Saltz, Chao Chen: "Topology-Guided Multi-Class Cell Context Generation for Digital Pathology", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023, (Acceptance rate of CVPR is 25.8%, paper).

  • Lu Pang, Tao Sun, Haibin Ling, Chao Chen: "Backdoor Cleansing with Unlabeled Data", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023, (Acceptance rate of CVPR is 25.8%, paper).

  • Xiaoling Hu, Dimitris Samaras, Chao Chen: "Learning Probabilistic Topological Representations Using Discrete Morse Theory", in the International Conference on Learning Representations (ICLR), 2023 (Spotlight, acceptance rate for oral/spotlight is 7.5%, paper)

  • Chen Li, Xiaoling Hu, Chao Chen: "Confidence Estimation Using Unlabeled Data", in the International Conference on Learning Representations (ICLR), 2023 (acceptance rate 32%, paper)

  • Jiachen Yao, Yikai Zhang, Songzhu Zheng, Mayank Goswami, Prateek Prasanna, Chao Chen: "Learning to Segment from Noisy Annotations: A Spatial Correction Approach", in the International Conference on Learning Representations (ICLR), 2023 (acceptance rate 32%, paper)

  • Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen: "Neural Approximation of Extended Persistent Homology on Graphs", in the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022 (paper, acceptance rate 25.6%)

  • Saumya Gupta, Xiaoling Hu, James Kaan, Michael Jin, Mutshipay Mpoy, Katherine Chung, Gagandeep Singh, Mary Saltz, Tahsin Kurc, Joel Saltz, Apostolos Tassiopoulos, Prateek Prasanna and Chao Chen: "Learning Topological Interactions for Multi-Class Medical Image Segmentation", in European Conference on Computer Vision (ECCV), 2022 (Oral presentation, acceptance rate 2.7%, paper)

  • Weimin Lyu, Xinyu Dong, Rachel Wong, Songzhu Zheng, Kayley Abell-Hart, Fusheng Wang and Chao Chen: "A Multimodal Transformer: Fusing Clinical Notes with Structured EHR Data for Interpretable In-Hospital Mortality Prediction", in Proceedings of AMIA Annual Symposium (AMIA), 2022

  • Lujain Alsaleh, Chen Li, Justin L. Couetil, Kun Huang, Jie Zhang, Chao Chen and Travis S. Johnson: "Spatial transcriptomic analysis reveals associations between genes and cellular topology in breast and prostate cancers", in International Conference on Intelligent Biology and Medicine (ICIBM), 2022

  • Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang and Chao Chen: "Cycle Representation Learning for Inductive Relation Prediction", in International Conference on Machine Learning (ICML), 2022 (acceptance rate 21.9%, paper, poster)

  • Weimin Lyu, Songzhu Zheng, Tengfei Ma, Chao Chen: "A Study of the Attention Abnormality in Trojaned BERTs", in The 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022 (acceptance rate 26%, paper).

  • Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pritham Pingali, Chao Chen, Mayank Goswami: "Stability of SGD: Tightness Analysis and Improved Bounds", in The Conference on Uncertainty in Artificial Intelligence (UAI), 2022

  • Aishik Konwer, Xuan Xu, Joseph Bae, Chao Chen, Prateek Prasanna: "Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022, (Oral Presentation, the overall acceptance rate of CVPR is 25.33%).

  • Fan Wang, Hubert Wagner, Chao Chen: "GPU Computation of the Euler Characteristic Curve for Imaging Data", in International Symposium on Computational Geometry (SoCG), 2022.

  • Xiaoling Hu, Xiao Lin, Michael Cogswell, Yi Yao, Susmit Jha, Chao Chen: "Trigger Hunting with a Topological Prior for Trojan Detection", in the International Conference on Learning Representations (ICLR), 2022

  • Wenjia Zhang, Yikai Zhang, Xiaoling Hu, Mayank Goswami, Chao Chen, Dimitris Metaxas: "A Manifold View of Adversarial Risk", in International Conference on Artificial Intelligence and Statistics (AISTATS), 2022

  • Songzhu Zheng, Yikai Zhang, Hubert Wagner, Mayank Goswami, Chao Chen: "Topological Detection of Trojaned Neural Networks", in the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), 2021, (acceptance rate 26%)

  • Shahira Abousamra, David Belinsky, John Van Arnam, Felicia Allard, Eric Yee,Rajarsi Gupta, Tahsin Kurc, Dimitris Samaras, Joel Saltz, Chao Chen: "Multi-Class Cell Detection Using Spatial Context Representation", in International Conference on Computer Vision (ICCV), 2021 (Oral, acceptance rate 3%)

  • Jiaqi Yang, Xiaoling Hu, Chao Chen, Chialing Tsai: "A Topological-Attention ConvLSTM Network and Its Application to EM Images", in the 24th International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI), 2021 (acceptance rate 32.7%)

  • Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang and Chao Chen: "Persistence Homology for Link Prediction: An Interactive View", in International Conference on Machine Learning (ICML), 2021 (acceptance rate 21.5%, paper)

  • Fan Wang, Saarthak Kapse, Steven Liu, Prateek Prasanna, and Chao Chen: "TopoTxR: A Topological Biomarker for Predicting Treatment Response in Breast Cancer", in international conference on Information Processing in Medical Imaging (IPMI), 2021

  • Aishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali, Jeremy Green, Tej Phatak, Amit Gupta, Chao Chen, Joel Saltz, Prateek Prasanna: "Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder Network", in Medical Imaging with Deep Learning(MIDL), 2021

  • Xiaoling Hu, Yusu Wang, Li Fuxin, Dimitris Samaras, Chao Chen: "Topology-Aware Segmentation Using Discrete Morse Theory", in the Nineth International Conference on Learning Representations (ICLR), 2021, (Spotlight, acceptance rate for spotlight+oral = 5.6%)

  • Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Mayank Goswami, Chao Chen: "Learning with feature dependent label noise: a progressive approach", in the Nineth International Conference on Learning Representations (ICLR), 2021, (Spotlight, acceptance rate for spotlight+oral = 5.6%)

  • Jiaqi Yang, Xiaoling Hu, Chao Chen , Chia-Ling Tsai: "3D Topology-Preserving Segmentation with Compound Multi-Slice Representation", in IEEE International Symposium on Biomedical Imaging (ISBI), 2021

  • Shahira Abousamra, Minh Hoai Nguyen, Dimitris Samaras, Chao Chen: "Localization in the Crowd with Topological Constraints", in The 35th AAAI Conference in Artificial Intelligence (AAAI), 2021, (acceptance rate 21%)

  • Pengxiang Wu, Songzhu Zheng, Mayank Goswami, Dimitris Metaxas, Chao Chen: "A Topological Filter for Learning with Label Noise", in the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), 2020, (acceptance rate 20.1%)

  • Jialin Yuan, Chao Chen, Li Fuxin: "Deep Variational Instance Segmentation", in the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), 2020, (acceptance rate 20.1%)

  • Cong Chen, Jiaqi Yang, Chao Chen and Changhe Yuan: "Solving Multiple Inference by Minimizing Expected Loss", in the 10th international conference on probabilistic graphical models (pgm), 2020.

  • Cong Chen, Changhe Yuan, Chao Chen: "efficient heuristic search for m-modes inference", in the 10th international conference on probabilistic graphical models (pgm), 2020.

  • Fan Wang, Huidong Liu, Dimitris Samaras, Chao Chen: "TopoGAN: A Topology-Aware Generative Adversarial Network", in European Conference on Computer Vision(ECCV), 2020, (paper, supplemental material, Oral, acceptance rate 2.1%).

  • Hui Qu, Yikai Zhang, Qi Chang, Zhennan Yan, Chao Chen, Dimitris Metaxas: "Learn distributed GAN with Temporary Discriminators", in European Conference on Computer Vision(ECCV), 2020, (acceptance rate 27.1%).

  • Songzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami, Dimitris Metaxas, Chao Chen: "Error-Bounded Correction of Noisy Labels", in International Conference on Machine Learning (ICML), 2020, (acceptance rate 21.8%).

  • Andrew Aukerman, Mathieu Carrière, Chao Chen, Kevin Gardner, Raúl Rabadán, Rami Vanguri: "Persistent Homology Based Characterization ofthe Breast Cancer Immune Microenvironment: A Feasibility Study", in International Symposium on Computational Geometry (SoCG), 2020.

  • Qi Chang, Hui Qu, Yikai Zhang, Mert Sabuncu, Chao Chen, Tong Zhang, Dimitris Metaxas: "Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020, (acceptance rate 22.1%).

  • Shahira Abousamra, Danielle Fassler, Le Hou, Yuwei Zhang, Rajarsi Gupta, Tahsin Kurc, Luisa F. Escobar-Hoyos, Dimitris Samaras, Beatrice Knudson, Kenneth Shroyer, Joel Saltz, Chao Chen: "Weakly-Supervised Deep Stain Decomposition for Multiplex IHC Images", in IEEE International Symposium on Biomedical Imaging (ISBI), 2020

  • Qi Zhao, Ze Ye, Yusu Wang, Chao Chen: "Persistence Enhanced Graph Neural Network", in International Conference on Artificial Intelligence and Statistics (AISTATS), 2020

  • Ze Ye, Kin Sum Liu, Tengfei Ma, Jie Gao, Chao Chen: "Curvature Graph Network", in the Eighth International Conference on Learning Representations(ICLR), 2020, (pdf, code, acceptance rate 26.5%).

  • Yikai Zhang, Hui Qu, Dimitris Metaxas, Chao Chen: "Local Regularizer Improves Generalization", in The 34th AAAI Conference in Artificial Intelligence (AAAI), 2020, (acceptance rate 20.6%)

  • Xiaoling Hu, Fuxin Li, Dimitris Samaras, Chao Chen: "Topology-Preserving Deep Image Segmentation", in the Thirty-third Conference on Neural Information Processing Systems (NeurIPS), 2019, (acceptance rate 21.2%)

  • Xiuyan Ni, Yang Yu, Peng Wu, Youlin Li, Shaoliang Nie, Qichao Que, Chao Chen: "Feature Selection for Facebook Feed Ranking System via a Group-Sparsity-Regularized Training Algorithm", in The 28th ACM International Conference on Information and Knowledge Management (CIKM), 2019

  • Ze Ye, Cong Chen, Changhe Yuan, Chao Chen: "Diverse Multiple Prediction on Neural Image Reconstruction", in the 22st International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI), 2019, (Early Acceptance)

  • Yikai Zhang, Hui Qu, Chao Chen, Dimitris Metaxas:"Taming the Noisy Gradient: Train Deep Neural Networks with Small Batch Sizes", in the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019, (acceptance rate 17.9%)

  • Xudong Zhang, Pengxiang Wu, Changhe Yuan, Yusu Wang, Dimitris Metaxas, Chao Chen: "Heuristic Search for Homology Localization Problem and Its Application in Cardiac Trabeculae Reconstruction", in the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019, (acceptance rate 17.9%)

  • Chao Chen, Xiuyan Ni, Qinxun Bai, Yusu Wang: "A Topological Regularizer for Classifiers via Persistent Homology", in International Conference on Artificial Intelligence and Statistics (AISTATS), 2019

  • Pengxiang Wu, Hui Qu, Jingru Yi, Qiaoying Huang, Chao Chen, Dimitris Metaxas: "Deep Attentive Feature Learning for Histopathology Image Classification", in IEEE International Symposium on Biomedical Imaging (ISBI), 2019

  • Pengxiang Wu, Chao Chen, Jingru Yi, Dimitris Metaxas: "Point Cloud Processing via Recurrent Set Encoding", in The 33rd AAAI Conference in Artificial Intelligence (AAAI), 2019, (acceptance rate 16.2%)

  • Cong Chen, Changhe Yuan, Ze Ye, Chao Chen: "Solving M-Modes in Loopy Graphs Using Tree Decompositions", in The 9th International Conference on Probabilistic Graphical Models (PGM), 2018.

  • Xiuyan Ni, Zhennan Yan, Tingting Wu, Jin Fan, Chao Chen: "A Region-of-Interest-Reweight 3D Convolutional Neural Network for the Analytics of Brain Information Processing", in the 21st International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI), 2018, (Oral Presentation, Acceptance Rate 4%).

  • Xiuyan Ni, Novi Quadrianto, Yusu Wang, Chao Chen: "Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data", in the 34rd International Conference on Machine Learning (ICML), 2017, (acceptance rate 25.46%) (pdf)

  • Pengxiang Wu, Chao Chen, Yusu Wang, Shaoting Zhang, Changhe Yuan, Zhen Qian, Dimitris Metaxas, Leon Axel: "Optimal Topological Cycles and Their Application in Cardiac Trabeculae Restoration", in the 25th biennial international conference on Information Processing in Medical Imaging (IPMI), 2017, (Oral presentation, acceptance rate 14.32%, pdf, code)

  • Chao Chen, Dimitris Metaxas, Yusu Wang, Pengxiang Wu: "Cardiac Trabeculae Segmentation, an Application of Computational Topology", in the 33rd International Symposium on Computational Geometry (SoCG): Multimedia Session, 2017, (pdf, video)

  • Chao Chen, Novi Quadrianto: "Clustering High Dimensional Categorical Data via Topographical Features", in the 33rd International Conference on Machine Learning (ICML), 2016, (acceptance rate 24.26%) (pdf)

  • Cong Chen, Changhe Yuan, Chao Chen: "Solving M-Modes Using Heuristic Search", in the 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016 (pdf)

  • Scott Kulp, Chao Chen, Dimitris Metaxas, Leon Axel: "Ventricular blood flow analysis using topological methods", in International Symposium on Biomedical Imaging (ISBI), 2015 (pdf)

  • Chao Chen, Han Liu, Dimitris Metaxas, Tianqi Zhao: "Mode Estimation for High Dimensional Discrete Tree Graphical Models", in Advances in Neural Information Processing Systems (NIPS), 2014 (Spotlight oral, acceptance rate ~5%, pdf, technical report available soon)

  • Mustafa Uzunbas, Chao Chen, Dimitris Metaxas: "Optree: a Learning-Based Adaptive Watershed Algorithm for Neuron Segmentation", in the 17th Annual International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2014. (Early acceptance rate ~10%, pdf)

  • Mingchen Gao, Chao Chen, Shaoting Zhang, Zhen Qian, Mani Vannan, Sarah Rinehart, Dimitris Metaxas, Leon Axel: "Morphological analysis of the papillary muscles and the trabaculae", in International Symposium on Biomedical Imaging (ISBI), 2014 (pdf)

  • Mustafa Uzunbas, Chao Chen, Shaoting Zhang, Kilian Pohl, Kang Li, Dimitris Metaxas: "Collaborative multi organ segmentation by integrating deformable and graphical models", in International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2013 (pdf)

  • Mingchen Gao *, Chao Chen *, Shaoting Zhang, Zhen Qian, Dimitris Metaxas, Leon Axel: "Segmenting the papillary muscles and the trabeculae from high resolution cardiac CT through restoration of topological handles", in International Conference on Information Processing in Medical Imaging (IPMI), 2013 (pdf) (* contributed equally)

  • Chao Chen, Vladimir Kolmogorov, Yan Zhu, Dimitris Metaxas, Christoph Lampert: "Computing the M most probable modes of a graphical model", in International Conference on Artificial Intelligence and Statistics (AISTATS), 2013 (Oral presentation, acceptance rate ~11% pdf, supplemental material)

  • Novi Quadrianto, Chao Chen, Christoph Lampert: "The most persistent soft-clique in a set of sampled graphs", in International Conference on Machine Learning (ICML), 2012 (pdf)

  • Oleksiy Busaryev, Sergio Cabello, Chao Chen, Tamal K. Dey, Yusu Wang: "Annotating simplices with a homology basis and its applications", in Scandinavian Symposium and Workshops on Algorithm Theory (SWAT), 2012 (pdf)

  • Chao Chen, Herbert Edelsbrunner: "Diffusion runs low on persistence fast", in IEEE International Conference on Computer Vision (ICCV), 2011 (Acceptance rate 23.7%, pdf, poster, code)

  • Chao Chen, Daniel Freedman, Christoph H. Lampert: "Enforcing topological constraints in random field image segmentation", in IEEE Computer Vision and Pattern Recognition (CVPR), 2011 (pdf, technical report, poster, code)

  • Chao Chen, Michael Kerber: "An output-sensitive algorithm for persistent homology", in Annual Symposium on Computational Geometry (SoCG), 2011 (pdf)

  • Chao Chen, Daniel Freedman: "Hardness results for homology localization", in Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2010 (pdf)

  • Chao Chen, Daniel Freedman: "Quantifying homology classes", in Annual Symposium on Theoretical Aspects of Computer Science (STACS), 2008 (pdf)
    Note: Proofs of the NP-hardness results in this paper are available in "Quantifying homology classes II: localization and stability".

Journals and Book Chapters

  • Danielle J Fassler, Shahira Abousamra, Rajarsi Gupta, Chao Chen, Maozheng Zhao, David Paredes, Syeda Areeha Batool, Beatrice S Knudsen, Luisa Escobar-Hoyos, Kenneth R Shroyer, Dimitris Samaras, Tahsin Kurc, Joel Saltz: "Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images", in Diagnostic pathology, 2020

  • Tingting Wu, Alfredo Spagna, Chao Chen, Kurt P. Schulz, Patrick R. Hof, and Jin Fan: "Supramodal Mechanisms of the Cognitive Control Network in Uncertainty Processing.", in Cerebral Cortex, 2020

  • W. Zheng, T. Eilamstock, T. Wu, A. Spagna, Chao Chen, B. Hu, J. Fan: "Multi-feature based network revealing the structural abnormalities in autism spectrum disorder", in IEEE Transactions on Affective Computing, 2019

  • Suwichaya Suwanwimolkul, Lei Zhang, Dong Gong, Zhen Zhang, Chao Chen, Damith C. Ranasinghe, Qinfeng Shi: "An Adaptive Markov Random Field for Structured Compressive Sensing", in IEEE Transactions on Image Processing (TIP), 2019

  • Tingting Wu, Alexander J. Dufford, Laura J. Egan, Melissa-Ann Mackie, Cong Chen, Changhe Yuan, Chao Chen, Xiaobo Li, Xun Liu, Patrick R. Hof, Jin Fan: "Hick–Hyman Law is Mediated by the Cognitive Control Network in the Brain", in Cerebral Cortex pp. 1-16, May 2017 (pdf)

  • Jingjing Liu, Chao Chen, Yan Zhu, Wei Liu, Dimitris Metaxas: “Video Classification via Weakly Supervised Sequence Modeling”, in Computer Vision and Image Understanding (CVIU) 152 pp. 79-87, Nov. 2016 (pdf)

  • Mustafa Uzunbas, Chao Chen, Dimitris Metaxas: “ An efficient conditional random field approach for automatic and interactive neuron segmentation”, in Medical Image Analysis (MedIA) 27 pp. 31-44, Jan. 2016 (pdf)

  • Arjun Jain, Chao Chen, Thorsten Thormählen, Dimitris Metaxas, Hans-Peter Seidel: “Multi-layer stencil creation from images”, in Computer & Graphics (C&G) 48 pp. 11-22, 2015 (pdf, video, website)

  • Chao Chen, Michael Kerber: “An output-sensitive algorithm for persistent homology”, in Computational Geometry: Theory and Applications (CGTA) 46 (4) pp. 435-447 - Special Issue on the 27th Annual Symposium on Computational Geometry, 2013 (pdf)

  • Yu Sheng, Barbara Cutler, Chao Chen, Joshua Nasman: "Perceptual global illumination cancellation in complex projection environments", in Computer Graphics Forum (CGF), Volume 30, Issue 4, Eurographics Symposium on Rendering (EGSR), 2011 (pdf)

  • Daniel Freedman, Chao Chen: "Algebraic topology for computer vision", Chapter 5 of Computer Vision, 239-268, Ed. Sota R. Yoshida, Nova Science Pub. Inc., Hauppauge, New York, 2011 (pdf)

  • Chao Chen, Daniel Freedman: "Hardness results for homology localization", in Discrete & Computational Geometry (DCG) 45(3): 425-448, 2011 (pdf)

  • Chao Chen, Daniel Freedman: "Measuring and computing natural generators for homology groups", in Computational Geometry: Theory and Applications (CGTA) 43(2): 169-181, 2010 (pdf)

  • Chao Chen, Ho-Lun Cheng: "Superimposing voronoi complexes for shape deformation", in International Journal of Computational Geometry and Applications (IJCGA) 16(2-3): 159-174 2006

Workshops

  • Chao Chen, Dimitris Metaxas, Yusu Wang, Pengxiang Wu, Changhe Yuan: "Cardiac Trabeculae Segmentation: an Application of Computational Topology", in the 27th Annual Fall Workshop on Computational Geometry (FWCG), 2017

  • Chao Chen, Han Liu, Dimitris Metaxas, Tianqi Zhao: "Identifying Sub-Networks of Functional Connectivity Using Modes of Distributions", in the 4th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI), 2014

  • Hubert Wagner, Chao Chen, Erald Vuçini: "Efficient computation of persistent homology for cubical data", in Proceedings of the 4th Workshop on Topology-based Methods in Data Analysis and Visualization (TopoInVis), 2011 (Best paper runner-up, pdf)

  • Chao Chen, Michael Kerber: "Persistent homology computation with a twist", in European Workshop on Computational Geometry (EuroCG), 2011 (pdf)

  • Chao Chen, Daniel Freedman: "Topology noise removal for curve and surface evolution", in Proceedings of the Medical Computer Vision Workshop (MCV) (in conjunction with MICCAI), 2010