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ORCIDBei Wang 0001
Bei Wang Phillips
Person information
- affiliation: University of Utah, Scientific Computing and Imaging Institute, Salt Lake City, UT, USA
Other persons with the same name
- Bei Wang — disambiguation page
- Bei Wang 0002
![[0000-0003-4942-9652]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-4942-9652")
— Princeton University, USA - Bei Wang 0003 — East China University of Science and Technology, Key Laboratory of Advanced Control and Optimization for Chemical Processes, Department of Automation, China
- Bei Wang 0004 — SenseTime, Shanghai, China (and 1 more)
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Journal Articles
- 2024
[j45]Fangfei Lan, Brandi Gamelin, Lin Yan, Jiali Wang, Bei Wang, Hanqi Guo:
Topological Characterization and Uncertainty Visualization of Atmospheric Rivers. Comput. Graph. Forum 43(3) (2024)- [j44]Peter Rottmann, Peter J. Rodgers, Xinyuan Yan, Daniel Archambault, Bei Wang, Jan-Henrik Haunert:
Generating Euler Diagrams Through Combinatorial Optimization. Comput. Graph. Forum 43(3) (2024) - [j43]Archit Rathore, Sunipa Dev, Jeff M. Phillips, Vivek Srikumar, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei Zhang, Bei Wang:
VERB: Visualizing and Interpreting Bias Mitigation Techniques Geometrically for Word Representations. ACM Trans. Interact. Intell. Syst. 14(1): 3:1-3:34 (2024) - [j42]Lin Yan, Hanqi Guo, Thomas Peterka, Bei Wang, Jiali Wang:
TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones. IEEE Trans. Vis. Comput. Graph. 30(1): 1249-1259 (2024) - [j41]Lin Yan, Xin Liang, Hanqi Guo, Bei Wang:
TopoSZ: Preserving Topology in Error-Bounded Lossy Compression. IEEE Trans. Vis. Comput. Graph. 30(1): 1302-1312 (2024) - 2023
- [j40]Lin Yan, Paul Aaron Ullrich, Luke P. Van Roekel, Bei Wang, Hanqi Guo:
Multilevel Robustness for 2D Vector Field Feature Tracking, Selection and Comparison. Comput. Graph. Forum 42(6) (2023) - [j39]Archit Rathore, Yichu Zhou, Vivek Srikumar, Bei Wang:
TopoBERT: Exploring the topology of fine-tuned word representations. Inf. Vis. 22(3): 186-208 (2023) - [j38]Youjia Zhou, Archit Rathore, Emilie Purvine, Bei Wang:
Topological Simplifications of Hypergraphs. IEEE Trans. Vis. Comput. Graph. 29(7): 3209-3225 (2023) - [j37]Lin Yan, Talha Bin Masood, Farhan Rasheed, Ingrid Hotz, Bei Wang:
Geometry-Aware Merge Tree Comparisons for Time-Varying Data With Interleaving Distances. IEEE Trans. Vis. Comput. Graph. 29(8): 3489-3506 (2023) - 2022
- [j36]Kevin P. Knudson, Bei Wang:
Discrete Stratified Morse Theory. Discret. Comput. Geom. 67(4): 1023-1052 (2022) - [j35]Tushar M. Athawale, Dan Maljovec, Lin Yan, Chris R. Johnson, Valerio Pascucci, Bei Wang:
Uncertainty Visualization of 2D Morse Complex Ensembles Using Statistical Summary Maps. IEEE Trans. Vis. Comput. Graph. 28(4): 1955-1966 (2022) - [j34]Daniel Klötzl, Tim Krake, Youjia Zhou, Ingrid Hotz, Bei Wang, Daniel Weiskopf:
Local bilinear computation of Jacobi sets. Vis. Comput. 38(9): 3435-3448 (2022) - 2021
- [j33]Archit Rathore, Nithin Chalapathi, Sourabh Palande, Bei Wang:
TopoAct: Visually Exploring the Shape of Activations in Deep Learning. Comput. Graph. Forum 40(1): 382-397 (2021) - [j32]Lin Yan, Talha Bin Masood, Raghavendra Sridharamurthy, Farhan Rasheed, Vijay Natarajan, Ingrid Hotz, Bei Wang:
Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization. Comput. Graph. Forum 40(3): 599-633 (2021) - [j31]Fangfei Lan, Michael Young, Lauren Anderson, Anders Ynnerman, Alexander Bock, Michelle A. Borkin, Angus G. Forbes, Juna A. Kollmeier, Bei Wang:
Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, and Educating the Earth. Comput. Graph. Forum 40(3): 635-663 (2021) - [j30]Adam Brown, Bei Wang:
Sheaf-Theoretic Stratification Learning from Geometric and Topological Perspectives. Discret. Comput. Geom. 65(4): 1166-1198 (2021) - [j29]Adam Brown, Omer Bobrowski, Elizabeth Munch, Bei Wang:
Probabilistic convergence and stability of random mapper graphs. J. Appl. Comput. Topol. 5(1): 99-140 (2021) - 2020
- [j28]Roxana Bujack, Lin Yan, Ingrid Hotz, Christoph Garth, Bei Wang:
State of the Art in Time-Dependent Flow Topology: Interpreting Physical Meaningfulness Through Mathematical Properties. Comput. Graph. Forum 39(3): 811-835 (2020) - [j27]Yuan Wang, Bei Wang:
Topological inference of manifolds with boundary. Comput. Geom. 88: 101606 (2020) - [j26]Michael J. Catanzaro, Justin Michael Curry, Brittany Terese Fasy, Janis Lazovskis, Greg Malen, Hans Riess, Bei Wang, Matthew Zabka:
Moduli spaces of morse functions for persistence. J. Appl. Comput. Topol. 4(3): 353-385 (2020) - [j25]Michal Adamaszek, Henry Adams, Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang, Lori Ziegelmeier:
On homotopy types of Vietoris-Rips complexes of metric gluings. J. Appl. Comput. Topol. 4(3): 425-454 (2020) - [j24]Braxton Osting, Sourabh Palande, Bei Wang:
Spectral sparsification of simplicial complexes for clustering and label propagation. J. Comput. Geom. 11(1): 176-211 (2020) - [j23]Ashley Suh, Mustafa Hajij, Bei Wang, Carlos Scheidegger, Paul Rosen:
Persistent Homology Guided Force-Directed Graph Layouts. IEEE Trans. Vis. Comput. Graph. 26(1): 697-707 (2020) - [j22]Lin Yan, Yusu Wang, Elizabeth Munch, Ellen Gasparovic, Bei Wang:
A Structural Average of Labeled Merge Trees for Uncertainty Visualization. IEEE Trans. Vis. Comput. Graph. 26(1): 832-842 (2020) - 2019
- [j21]Sourabh Palande, Vipin Jose, Brandon A. Zielinski, Jeffrey S. Anderson, P. Thomas Fletcher, Bei Wang:
Revisiting Abnormalities in Brain Network Architecture Underlying Autism Using Topology-Inspired Statistical Inference. Brain Connect. 9(1): 13-21 (2019) - [j20]Jochen Jankowai, Bei Wang, Ingrid Hotz:
Robust Extraction and Simplification of 2D Symmetric Tensor Field Topology. Comput. Graph. Forum 38(3): 337-349 (2019) - [j19]René Corbet, Ulderico Fugacci, Michael Kerber, Claudia Landi, Bei Wang:
A kernel for multi-parameter persistent homology. Comput. Graph. X 2 (2019) - [j18]Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang, Lori Ziegelmeier:
The relationship between the intrinsic Čech and persistence distortion distances for metric graphs. J. Comput. Geom. 10(1): 477-499 (2019) - 2018
- [j17]Shusen Liu, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Vivek Srikumar, Bei Wang, Yarden Livnat, Valerio Pascucci:
Visual Exploration of Semantic Relationships in Neural Word Embeddings. IEEE Trans. Vis. Comput. Graph. 24(1): 553-562 (2018) - 2017
- [j16]William I. Gasarch, Brittany Terese Fasy, Bei Wang:
Open Problems in Computational Topology. SIGACT News 48(3): 32-36 (2017) - [j15]Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer, Valerio Pascucci:
Visualizing High-Dimensional Data: Advances in the Past Decade. IEEE Trans. Vis. Comput. Graph. 23(3): 1249-1268 (2017) - 2016
- [j14]Shusen Liu, Peer-Timo Bremer, J. J. Jayaraman, Bei Wang, Brian Summa, Valerio Pascucci:
The Grassmannian Atlas: A General Framework for Exploring Linear Projections of High-Dimensional Data. Comput. Graph. Forum 35(3): 1-10 (2016) - [j13]Dan Maljovec, Shusen Liu, Bei Wang, Diego Mandelli, Peer-Timo Bremer, Valerio Pascucci, Curtis L. Smith:
Analyzing simulation-based PRA data through traditional and topological clustering: A BWR station blackout case study. Reliab. Eng. Syst. Saf. 145: 262-276 (2016) - [j12]Attila Gyulassy, Aaron Knoll, Kah Chun Lau, Bei Wang, Peer-Timo Bremer, Michael E. Papka, Larry A. Curtiss, Valerio Pascucci:
Interstitial and Interlayer Ion Diffusion Geometry Extraction in Graphitic Nanosphere Battery Materials. IEEE Trans. Vis. Comput. Graph. 22(1): 916-925 (2016) - [j11]Primoz Skraba, Paul Rosen, Bei Wang, Guoning Chen, Harsh Bhatia, Valerio Pascucci:
Critical Point Cancellation in 3D Vector Fields: Robustness and Discussion. IEEE Trans. Vis. Comput. Graph. 22(6): 1683-1693 (2016) - 2015
- [j10]Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Valerio Pascucci:
Visual Exploration of High-Dimensional Data through Subspace Analysis and Dynamic Projections. Comput. Graph. Forum 34(3): 271-280 (2015) - [j9]Harsh Bhatia, Bei Wang, Gregory Norgard, Valerio Pascucci, Peer-Timo Bremer:
Local, smooth, and consistent Jacobi set simplification. Comput. Geom. 48(4): 311-332 (2015) - [j8]Peer-Timo Bremer, Dan Maljovec, Avishek Saha, Bei Wang, Jim Gaffney, Brian K. Spears, Valerio Pascucci:
ND2AV: N-dimensional data analysis and visualization analysis for the National Ignition Campaign. Comput. Vis. Sci. 17(1): 1-18 (2015) - [j7]Primoz Skraba, Bei Wang, Guoning Chen, Paul Rosen:
Robustness-Based Simplification of 2D Steady and Unsteady Vector Fields. IEEE Trans. Vis. Comput. Graph. 21(8): 930-944 (2015) - 2014
- [j6]Shusen Liu, Bei Wang, Peer-Timo Bremer, Valerio Pascucci:
Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data. Comput. Graph. Forum 33(3): 101-110 (2014) - 2013
- [j5]Bei Wang, Paul Rosen, Primoz Skraba, Harsh Bhatia, Valerio Pascucci:
Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields. Comput. Graph. Forum 32(3): 221-230 (2013) - 2011
- [j4]Bei Wang, Herbert Edelsbrunner, Dmitriy Morozov:
Computing elevation maxima by searching the gauss sphere. ACM J. Exp. Algorithmics 16 (2011) - [j3]Bei Wang, Brian Summa, Valerio Pascucci, Mikael Vejdemo-Johansson:
Branching and Circular Features in High Dimensional Data. IEEE Trans. Vis. Comput. Graph. 17(12): 1902-1911 (2011) - 2010
- [j2]Mats Ensterö, Örjan Åkerborg, Daniel Lundin, Bei Wang, Terrence S. Furey, Marie Öhman, Jens Lagergren:
A computational screen for site selective A-to-I editing detects novel sites in neuron specific Hu proteins. BMC Bioinform. 11: 6 (2010) - 2007
- [j1]Bei Wang, Dimitris Papamichail, Steffen Mueller, Steven Skiena:
Two proteins for the price of one: the design of maximally compressed coding sequences. Nat. Comput. 6(4): 359-370 (2007)
Conference and Workshop Papers
- 2024
- [c45]Qingsong Wang, Guanqun Ma, Raghavendra Sridharamurthy, Bei Wang:
Measure-Theoretic Reeb Graphs and Reeb Spaces. SoCG 2024: 80:1-80:18 - [c44]Xinyuan Yan, Peter Rodgers, Peter Rottmann, Daniel Archambault, Jan-Henrik Haunert, Bei Wang:
EulerMerge: Simplifying Euler Diagrams Through Set Merges. Diagrams 2024: 190-206 - [c43]Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Lio, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi:
Position: Topological Deep Learning is the New Frontier for Relational Learning. ICML 2024 - [c42]Zhichao Xu, Daniel Cohen, Bei Wang, Vivek Srikumar:
In-Context Example Ordering Guided by Label Distributions. NAACL-HLT (Findings) 2024: 2623-2640 - [c41]Xinyuan Yan, Youjia Zhou, Arul Mishra, Himanshu Mishra, Bei Wang:
Exploring Visualization for Fairness in AI Education. PacificVis 2024: 1-10 - [c40]Mengjiao Han, Jixian Li, Sudhanshu Sane, Shubham Gupta, Bei Wang, Steve Petruzza, Chris R. Johnson:
Interactive Visualization of Time-Varying Flow Fields Using Particle Tracing Neural Networks. PacificVis 2024: 52-61 - 2023
- [c39]Emilie Purvine, Davis Brown, Brett A. Jefferson, Cliff A. Joslyn, Brenda Praggastis, Archit Rathore, Madelyn Shapiro, Bei Wang, Youjia Zhou:
Experimental Observations of the Topology of Convolutional Neural Network Activations. AAAI 2023: 9470-9479 - [c38]Chedi Morchdi, Yi Zhou, Jie Ding, Bei Wang:
Exploring Gradient Oscillation in Deep Neural Network Training. Allerton 2023: 1-7 - [c37]Youjia Zhou, Yi Zhou, Jie Ding, Bei Wang:
Visualizing and Analyzing the Topology of Neuron Activations in Deep Adversarial Training. TAG-ML 2023: 134-145 - [c36]Mingzhe Li, Carson Storm, Austin Yang Li, Tom Needham, Bei Wang:
Comparing Morse Complexes Using Optimal Transport: An Experimental Study. IEEE VIS (Short Papers) 2023: 41-45 - 2022
- [c35]Fangfei Lan, Sourabh Palande, Michael Young, Bei Wang:
Uncertainty Visualization for Graph Coarsening. IEEE Big Data 2022: 2922-2931 - [c34]Bei Wang, Arul Mishra, Himanshu Mishra:
Humans as Mitigators of Biases in Risk Prediction via Field Studies. IEEE Big Data 2022: 5059-5067 - 2021
- [c33]Youjia Zhou, Nithin Chalapathi, Archit Rathore, Yaodong Zhao, Bei Wang:
Mapper Interactive: A Scalable, Extendable, and Interactive Toolbox for the Visual Exploration of High-Dimensional Data. PacificVis 2021: 101-110 - [c32]Youjia Zhou, Methun Kamruzzaman, Patrick S. Schnable, Bala Krishnamoorthy, Ananth Kalyanaraman, Bei Wang:
Pheno-mapper: an interactive toolbox for the visual exploration of phenomics data. BCB 2021: 20:1-20:10 - [c31]Nithin Chalapathi, Youjia Zhou, Bei Wang:
Adaptive Covers for Mapper Graphs Using Information Criteria. IEEE BigData 2021: 3789-3800 - [c30]Avishan Bagherinezhad, Michael Young, Bei Wang, Masood Parvania:
Spatio-Temporal Visualization of Interdependent Battery Bus Transit and Power Distribution Systems. ISGT 2021: 1-5 - [c29]Archit Rathore, Sunipa Dev, Jeff M. Phillips, Vivek Srikumar, Bei Wang:
A Visual Tour of Bias Mitigation Techniques for Word Representations. KDD 2021: 4064-4065 - [c28]Archit Rathore, Sunipa Dev, Vivek Srikumar, Jeff M. Phillips, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei Zhang, Bei Wang:
An Interactive Visual Demo of Bias Mitigation Techniques for Word Representations From a Geometric Perspective. NeurIPS (Competition and Demos) 2021: 330-335 - 2020
- [c27]Youjia Zhou, Kevin P. Knudson, Bei Wang:
Visual Demo of Discrete Stratified Morse Theory (Media Exposition). SoCG 2020: 82:1-82:4 - [c26]Han Han, Konstantinos Oikonomou, Nithin Chalapathi, Masood Parvania, Bei Wang:
Interactive Visualization of Interdependent Power and Water Infrastructure Operation. ISGT 2020: 1-5 - 2019
- [c25]Archit Rathore, Sourabh Palande, Jeffrey S. Anderson, Brandon A. Zielinski, P. Thomas Fletcher, Bei Wang:
Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale. MICCAI (3) 2019: 736-744 - 2018
- [c24]Mustafa Hajij, Bei Wang, Carlos Scheidegger, Paul Rosen:
Visual Detection of Structural Changes in Time-Varying Graphs Using Persistent Homology. PacificVis 2018: 125-134 - [c23]Michal Adamaszek, Henry Adams, Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang, Lori Ziegelmeier:
Vietoris-Rips and Cech Complexes of Metric Gluings. SoCG 2018: 3:1-3:15 - [c22]Adam Brown, Bei Wang:
Sheaf-Theoretic Stratification Learning. SoCG 2018: 14:1-14:14 - [c21]Kevin P. Knudson, Bei Wang:
Discrete Stratified Morse Theory: A User's Guide. SoCG 2018: 54:1-54:14 - [c20]Keri L. Anderson, Jeffrey S. Anderson, Sourabh Palande, Bei Wang:
Topological Data Analysis of Functional MRI Connectivity in Time and Space Domains. CNI@MICCAI 2018: 67-77 - 2017
- [c19]Wathsala Widanagamaachchi, Alexander Jacques, Bei Wang, Erik T. Crosman, Peer-Timo Bremer, Valerio Pascucci, John D. Horel:
Exploring the evolution of pressure-perturbations to understand atmospheric phenomena. PacificVis 2017: 101-110 - [c18]Sourabh Palande, Vipin Jose, Brandon A. Zielinski, Jeffrey S. Anderson, P. Thomas Fletcher, Bei Wang:
Revisiting Abnormalities in Brain Network Architecture Underlying Autism Using Topology-Inspired Statistical Inference. CNI@MICCAI 2017: 98-107 - 2016
- [c17]Dan Maljovec, Bei Wang, Paul Rosen, Andrea Alfonsi, Giovanni Pastore, Cristian Rabiti, Valerio Pascucci:
Rethinking sensitivity analysis of nuclear simulations with topology. PacificVis 2016: 64-71 - [c16]Elizabeth Munch, Bei Wang:
Convergence between Categorical Representations of Reeb Space and Mapper. SoCG 2016: 53:1-53:16 - [c15]Brittany Terese Fasy, Bei Wang:
Exploring persistent local homology in topological data analysis. ICASSP 2016: 6430-6434 - [c14]Eleanor Wong, Sourabh Palande, Bei Wang, Brandon A. Zielinski, Jeffrey S. Anderson, P. Thomas Fletcher:
Kernel partial least squares regression for relating functional brain network topology to clinical measures of behavior. ISBI 2016: 1303-1306 - [c13]Hoa Nguyen, Paul Rosen, Bei Wang:
Visual exploration of multiway dependencies in multivariate data. SIGGRAPH Asia Symposium on Visualization 2016: 2:1-2:8 - 2015
- [c12]Jeff M. Phillips, Bei Wang, Yan Zheng:
Geometric Inference on Kernel Density Estimates. SoCG 2015: 857-871 - [c11]Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer, Valerio Pascucci:
Visualizing High-Dimensional Data: Advances in the Past Decade. EuroVis (STARs) 2015: 127-147 - 2014
- [c10]Primoz Skraba, Bei Wang, Guoning Chen, Paul Rosen:
2D Vector Field Simplification Based on Robustness. PacificVis 2014: 49-56 - [c9]Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Valerio Pascucci:
Multivariate volume visualization through dynamic projections. LDAV 2014: 35-42 - [c8]Primoz Skraba, Bei Wang:
Approximating Local Homology from Samples. SODA 2014: 174-192 - 2012
- [c7]A. N. M. Imroz Choudhury, Bei Wang, Paul Rosen, Valerio Pascucci:
Topological analysis and visualization of cyclical behavior in memory reference traces. PacificVis 2012: 9-16 - [c6]Paul Bendich, Bei Wang, Sayan Mukherjee:
Local homology transfer and stratification learning. SODA 2012: 1355-1370 - 2010
- [c5]Paul Bendich, Sayan Mukherjee, Bei Wang:
Stratification Learning through Homology Inference. AAAI Fall Symposium: Manifold Learning and Its Applications 2010 - 2009
- [c4]Bei Wang, Herbert Edelsbrunner, Dmitriy Morozov:
Computing Elevation Maxima by Searching the Gauss Sphere. SEA 2009: 281-292 - 2008
- [c3]Bei Wang, Jeff M. Phillips, Robert Schreiber, Dennis M. Wilkinson:
Spatial Scan Statistics for Graph Clustering. SDM 2008: 727-738 - 2006
- [c2]Sudheer Sahu, Bei Wang, John H. Reif:
A Framework for Modeling DNA Based Molecular Systems. DNA 2006: 250-265 - 2005
- [c1]Bei Wang, Dimitris Papamichail, Steffen Mueller, Steven Skiena:
Two Proteins for the Price of One: The Design of Maximally Compressed Coding Sequences. DNA 2005: 387-398
Parts in Books or Collections
- 2020
- [p2]Ingrid Hotz, Roxana Bujack, Christoph Garth, Bei Wang:
Mathematical Foundations in Visualization. Foundations of Data Visualization 2020: 87-119 - 2014
- [p1]Primoz Skraba, Bei Wang:
Interpreting Feature Tracking Through the Lens of Robustness. Topological Methods in Data Analysis and Visualization 2014: 19-37
Editorship
- 2023
- [e1]Thomas Höllt, Wolfgang Aigner, Bei Wang:
25th Eurographics Conference on Visualization, EuroVis 2023 - Short Papers, Leipzig, Germany, June 12-16, 2023. Eurographics Association 2023, ISBN 978-3-03868-219-6 [contents]
Informal and Other Publications
- 2024
- [i59]Qingsong Wang, Guanquan Ma, Raghavendra Sridharamurthy, Bei Wang:
Measure Theoretic Reeb Graphs and Reeb Spaces. CoRR abs/2401.06748 (2024) - [i58]Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Liò, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi:
Position Paper: Challenges and Opportunities in Topological Deep Learning. CoRR abs/2402.08871 (2024) - [i57]Zhichao Xu, Daniel Cohen, Bei Wang, Vivek Srikumar:
In-Context Example Ordering Guided by Label Distributions. CoRR abs/2402.11447 (2024) - [i56]Yuxiao Li, Xin Liang, Bei Wang, Yongfeng Qiu, Lin Yan, Hanqi Guo:
MSz: An Efficient Parallel Algorithm for Correcting Morse-Smale Segmentations in Error-Bounded Lossy Compressors. CoRR abs/2406.09423 (2024) - [i55]Mingzhe Li, Hamish A. Carr, Oliver Rübel, Bei Wang, Gunther H. Weber:
Distributed Augmentation, Hypersweeps, and Branch Decomposition of Contour Trees for Scientific Exploration. CoRR abs/2408.04836 (2024) - [i54]Guanqun Ma, David Lenz, Tom Peterka, Hanqi Guo, Bei Wang:
Critical Point Extraction from Multivariate Functional Approximation. CoRR abs/2408.13193 (2024) - 2023
- [i53]Mingzhe Li, Xinyuan Yan, Lin Yan, Tom Needham, Bei Wang:
Flexible and Probabilistic Topology Tracking with Partial Optimal Transport. CoRR abs/2302.02895 (2023) - [i52]Lin Yan, Xin Liang, Hanqi Guo, Bei Wang:
TopoSZ: Preserving Topology in Error-Bounded Lossy Compression. CoRR abs/2304.11768 (2023) - [i51]Fangfei Lan, Salman Parsa, Bei Wang:
Labeled Interleaving Distance for Reeb Graphs. CoRR abs/2306.01186 (2023) - [i50]Erin W. Chambers, Elizabeth Munch, Sarah Percival, Bei Wang:
Bounding the Interleaving Distance for Geometric Graphs with a Loss Function. CoRR abs/2307.15130 (2023) - [i49]Lin Yan, Hanqi Guo, Thomas Peterka, Bei Wang, Jiali Wang:
TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones. CoRR abs/2307.15243 (2023) - [i48]Mingzhe Li, Carson Storm, Austin Yang Li, Tom Needham, Bei Wang:
Comparing Morse Complexes Using Optimal Transport: An Experimental Study. CoRR abs/2309.04681 (2023) - [i47]Xinyuan Yan, Peter Rodgers, Peter Rottmann, Daniel Archambault, Jan-Henrik Haunert, Bei Wang:
EulerMerge: Simplifying Euler Diagrams Through Set Merges. CoRR abs/2311.15396 (2023) - [i46]Mengjiao Han, Jixian Li, Sudhanshu Sane, Shubham Gupta, Bei Wang, Steve Petruzza, Chris R. Johnson:
Interactive Visualization of Time-Varying Flow Fields Using Particle Tracing Neural Networks. CoRR abs/2312.14973 (2023) - [i45]Ulrich Bauer, Vijay Natarajan, Bei Wang:
Topological Data Analysis and Applications (Dagstuhl Seminar 23192). Dagstuhl Reports 13(5): 71-95 (2023) - 2022
- [i44]Brenda Praggastis, Davis Brown, Carlos Ortiz Marrero, Emilie Purvine, Madelyn Shapiro, Bei Wang:
The SVD of Convolutional Weights: A CNN Interpretability Framework. CoRR abs/2208.06894 (2022) - [i43]Bhavana Doppalapudi, Bei Wang, Paul Rosen:
Untangling Force-Directed Layouts Using Persistent Homology. CoRR abs/2208.06927 (2022) - [i42]Daniel Klötzl, Tim Krake, Youjia Zhou, Jonathan Stober, Kathrin Schulte, Ingrid Hotz, Bei Wang, Daniel Weiskopf:
Reduced Connectivity for Local Bilinear Jacobi Sets. CoRR abs/2208.07148 (2022) - [i41]Lin Yan, Paul Aaron Ullrich, Luke P. Van Roekel, Bei Wang, Hanqi Guo:
Multilevel Robustness for 2D Vector Field Feature Tracking, Selection, and Comparison. CoRR abs/2209.11708 (2022) - [i40]Emilie Purvine, Davis Brown, Brett A. Jefferson, Cliff A. Joslyn, Brenda Praggastis, Archit Rathore, Madelyn Shapiro, Bei Wang, Youjia Zhou:
Experimental Observations of the Topology of Convolutional Neural Network Activations. CoRR abs/2212.00222 (2022) - 2021
- [i39]Mingzhe Li, Sourabh Palande, Bei Wang:
Sketching Merge Trees. CoRR abs/2101.03196 (2021) - [i38]Archit Rathore, Sunipa Dev, Jeff M. Phillips, Vivek Srikumar, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei Zhang, Bei Wang:
VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations. CoRR abs/2104.02797 (2021) - [i37]Youjia Zhou, Archit Rathore, Emilie Purvine, Bei Wang:
Topological Simplifications of Hypergraphs. CoRR abs/2104.11214 (2021) - [i36]Youjia Zhou, Nathaniel Saul, Ilkin Safarli, Bala Krishnamoorthy, Bei Wang:
Stitch Fix for Mapper and Information Gains. CoRR abs/2105.01961 (2021) - [i35]Fangfei Lan, Michael Young, Lauren Anderson, Anders Ynnerman, Alexander Bock, Michelle A. Borkin, Angus G. Forbes, Juna A. Kollmeier, Bei Wang:
Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, and Educating the Earth. CoRR abs/2106.00152 (2021) - [i34]Lin Yan, Talha Bin Masood, Raghavendra Sridharamurthy, Farhan Rasheed, Vijay Natarajan, Ingrid Hotz, Bei Wang:
Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization. CoRR abs/2106.00157 (2021) - [i33]Tushar M. Athawale, Alireza Entezari, Bei Wang, Chris R. Johnson:
Statistical Rendering for Visualization of Red Sea Eddy Simulation Data. CoRR abs/2106.12138 (2021) - [i32]Youjia Zhou, Methun Kamruzzaman, Patrick S. Schnable, Bala Krishnamoorthy, Ananth Kalyanaraman, Bei Wang:
Pheno-Mapper: An Interactive Toolbox for the Visual Exploration of Phenomics Data. CoRR abs/2106.13397 (2021) - [i31]Lin Yan, Talha Bin Masood, Farhan Rasheed, Ingrid Hotz, Bei Wang:
Geometry-Aware Merge Tree Comparisons for Time-Varying Data with Interleaving Distances. CoRR abs/2107.14373 (2021) - [i30]Samir Chowdhury, Tom Needham, Ethan Semrad, Bei Wang, Youjia Zhou:
Hypergraph Co-Optimal Transport: Metric and Categorical Properties. CoRR abs/2112.03904 (2021) - 2020
- [i29]Ilkin Safarli, Youjia Zhou, Bei Wang:
Interpreting Graph Drawing with Multi-Agent Reinforcement Learning. CoRR abs/2011.00748 (2020) - [i28]Youjia Zhou, Nithin Chalapathi, Archit Rathore, Yaodong Zhao, Bei Wang:
Mapper Interactive: A Scalable, Extendable, and Interactive Toolbox for the Visual Exploration of High-Dimensional Data. CoRR abs/2011.03209 (2020) - [i27]Avishan Bagherinezhad, Michael Young, Bei Wang, Masood Parvania:
Spatio-Temporal Visualization of Interdependent Battery Bus Transit and Power Distribution Systems. CoRR abs/2011.10917 (2020) - 2019
- [i26]Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang, Lori Ziegelmeier:
Local Versus Global Distances for Zigzag Persistence Modules. CoRR abs/1903.08298 (2019) - [i25]Ellen Gasparovic, Elizabeth Munch, Steve Oudot, Katharine Turner, Bei Wang, Yusu Wang:
Intrinsic Interleaving Distance for Merge Trees. CoRR abs/1908.00063 (2019) - [i24]Lin Yan, Yusu Wang, Elizabeth Munch, Ellen Gasparovic, Bei Wang:
A Structural Average of Labeled Merge Trees for Uncertainty Visualization. CoRR abs/1908.00113 (2019) - [i23]Adam Brown, Omer Bobrowski, Elizabeth Munch, Bei Wang:
Probabilistic Convergence and Stability of Random Mapper Graphs. CoRR abs/1909.03488 (2019) - [i22]Ingrid Hotz, Roxana Bujack, Christoph Garth, Bei Wang:
Mathematical Foundations in Visualization. CoRR abs/1909.04835 (2019) - [i21]Archit Rathore, Nithin Chalapathi, Sourabh Palande, Bei Wang:
TopoAct: Exploring the Shape of Activations in Deep Learning. CoRR abs/1912.06332 (2019) - [i20]Tushar M. Athawale, Dan Maljovec, Chris R. Johnson, Valerio Pascucci, Bei Wang:
Uncertainty Visualization of 2D Morse Complex Ensembles Using Statistical Summary Maps. CoRR abs/1912.06341 (2019) - [i19]Youjia Zhou, Janis Lazovskis, Michael J. Catanzaro, Matthew Zabka, Bei Wang:
MVF Designer: Design and Visualization of Morse Vector Fields. CoRR abs/1912.09580 (2019) - [i18]Michael Kerber, Vijay Natarajan, Bei Wang:
Topology, Computation and Data Analysis (Dagstuhl Seminar 19212). Dagstuhl Reports 9(5): 110-131 (2019) - 2018
- [i17]Kevin P. Knudson, Bei Wang:
Discrete Stratified Morse Theory: A User's Guide. CoRR abs/1801.03183 (2018) - [i16]Mustafa Hajij, Bei Wang, Paul Rosen:
MOG: Mapper on Graphs for Relationship Preserving Clustering. CoRR abs/1804.11242 (2018) - [i15]Lin Yan, Yaodong Zhao, Paul Rosen, Carlos Scheidegger, Bei Wang:
Homology-Preserving Dimensionality Reduction via Manifold Landmarking and Tearing. CoRR abs/1806.08460 (2018) - [i14]René Corbet, Ulderico Fugacci, Michael Kerber, Claudia Landi, Bei Wang:
A Kernel for Multi-Parameter Persistent Homology. CoRR abs/1809.10231 (2018) - [i13]Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang, Lori Ziegelmeier:
The Relationship Between the Intrinsic Cech and Persistence Distortion Distances for Metric Graphs. CoRR abs/1812.05282 (2018) - 2017
- [i12]Paul Rosen, Bei Wang, Anil Seth, Betsy Mills, Adam Ginsburg, Julia Kamenetzky, Jeff Kern, Chris R. Johnson:
Using Contour Trees in the Analysis and Visualization of Radio Astronomy Data Cubes. CoRR abs/1704.04561 (2017) - [i11]Mustafa Hajij, Bei Wang, Carlos Scheidegger, Paul Rosen:
Persistent Homology Guided Exploration of Time-Varying Graphs. CoRR abs/1707.06683 (2017) - [i10]Braxton Osting, Sourabh Palande, Bei Wang:
Towards Spectral Sparsification of Simplicial Complexes Based on Generalized Effective Resistance. CoRR abs/1708.08436 (2017) - [i9]Tim Sodergren, Jessica Hair, Jeff M. Phillips, Bei Wang:
Visualizing Sensor Network Coverage with Location Uncertainty. CoRR abs/1710.06925 (2017) - [i8]Ashley Suh, Mustafa Hajij, Bei Wang, Carlos Scheidegger, Paul Rosen:
Driving Interactive Graph Exploration Using 0-Dimensional Persistent Homology Features. CoRR abs/1712.05548 (2017) - [i7]Michal Adamaszek, Henry Adams, Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang, Lori Ziegelmeier:
Vietoris-Rips and Cech Complexes of Metric Gluings. CoRR abs/1712.06224 (2017) - [i6]Adam Brown, Bei Wang:
Sheaf-Theoretic Stratification Learning. CoRR abs/1712.07734 (2017) - [i5]Hamish A. Carr, Michael Kerber, Bei Wang:
Topology, Computation and Data Analysis (Dagstuhl Seminar 17292). Dagstuhl Reports 7(7): 88-109 (2017) - 2015
- [i4]Elizabeth Munch, Bei Wang:
Convergence between Categorical Representations of Reeb Space and Mapper. CoRR abs/1512.04108 (2015) - 2013
- [i3]Harsh Bhatia, Bei Wang, Gregory Norgard, Valerio Pascucci, Peer-Timo Bremer:
Local, Smooth, and Consistent Jacobi Set Simplification. CoRR abs/1307.7752 (2013) - [i2]Jeff M. Phillips, Bei Wang, Yan Zheng:
Geometric Inference on Kernel Density Estimates. CoRR abs/1307.7760 (2013) - 2012
- [i1]Primoz Skraba, Bei Wang:
Sampling for Local Homology with Vietoris-Rips Complexes. CoRR abs/1206.0834 (2012)
Coauthor Index
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