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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://dblp1.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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2020 – today
- 2023
[j37]Youjia Zhou, Archit Rathore, Emilie Purvine, Bei Wang:
Topological Simplifications of Hypergraphs. IEEE Trans. Vis. Comput. Graph. 29(7): 3209-3225 (2023)- [i44]Mingzhe Li, Xinyuan Yan, Lin Yan, Tom Needham, Bei Wang:
Flexible and Probabilistic Topology Tracking with Partial Optimal Transport. CoRR abs/2302.02895 (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) - [c35]Fangfei Lan, Sourabh Palande, Michael Young, Bei Wang:
Uncertainty Visualization for Graph Coarsening. Big Data 2022: 2922-2931 - [c34]Bei Wang, Arul Mishra, Himanshu Mishra:
Humans as Mitigators of Biases in Risk Prediction via Field Studies. Big Data 2022: 5059-5067 - [i43]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) - [i42]Bhavana Doppalapudi, Bei Wang, Paul Rosen:
Untangling Force-Directed Layouts Using Persistent Homology. CoRR abs/2208.06927 (2022) - [i41]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) - [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
- [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) - [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 - [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
- [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 M. 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) - [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 - [p2]Ingrid Hotz, Roxana Bujack, Christoph Garth, Bei Wang:
Mathematical Foundations in Visualization. Foundations of Data Visualization 2020: 87-119 - [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)
2010 – 2019
- 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) - [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 - [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
- [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) - [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 - [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
- [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) - [c19]Wathsala Widanagamaachchi, Alexander Jacques, Bei Wang, Erik 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 - [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) - 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 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) - [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
- [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) - [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 - [i4]Elizabeth Munch, Bei Wang:
Convergence between Categorical Representations of Reeb Space and Mapper. CoRR abs/1512.04108 (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) - [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 - [p1]Primoz Skraba, Bei Wang:
Interpreting Feature Tracking Through the Lens of Robustness. Topological Methods in Data Analysis and Visualization 2014: 19-37 - 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) - [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
- [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 - [i1]Primoz Skraba, Bei Wang:
Sampling for Local Homology with Vietoris-Rips Complexes. CoRR abs/1206.0834 (2012) - 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) - [c5]Paul Bendich, Sayan Mukherjee, Bei Wang:
Stratification Learning through Homology Inference. AAAI Fall Symposium: Manifold Learning and Its Applications 2010
2000 – 2009
- 2009
- [c4]Bei Wang, Herbert Edelsbrunner, Dmitriy Morozov:
Computing Elevation Maxima by Searching the Gauss Sphere. SEA 2009: 281-292 - 2008
- [c3]