Joshua T. Vogelstein

ORCID

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 98

Top Venues

CoRR

NeuroImage

J. Mach. Learn. Res.

IEEE Trans. Pattern Anal. Mach. Intell.

Publications

Thomas L. Athey, Daniel Jacob Tward, Ulrich Mueller, Laurent Younes, Joshua T. Vogelstein, Michael I. Miller
Preserving Derivative Information while Transforming Neuronal Curves. Neuroinformatics 22 (1) (2024)
Cencheng Shen, Jaewon Chung, Ronak D. Mehta, Ting Xu, Joshua T. Vogelstein
Independence Testing for Temporal Data. Trans. Mach. Learn. Res. 2024 (2024)
Cencheng Shen, Shangsi Wang, Alexandra Badea, Carey E. Priebe, Joshua T. Vogelstein
Discovering the signal subgraph: An iterative screening approach on graphs. Pattern Recognit. Lett. 184 (2024)
Meghana Madhyastha, Tamas Budavari, Vladimir Braverman, Joshua T. Vogelstein, Randal C. Burns
T-Rex (Tree-Rectangles): Reformulating Decision Tree Traversal as Hyperrectangle Enclosure. ICDE (2024)
Ashwin De Silva, Rahul Ramesh, Carey E. Priebe, Pratik Chaudhari, Joshua T. Vogelstein
The Value of Out-of-Distribution Data. ICML (2023)
Hayden S. Helm, Amitabh Basu, Avanti Athreya, Youngser Park, Joshua T. Vogelstein, Carey E. Priebe, Michael Winding, Marta Zlatic, Albert Cardona, Patrick Bourke, Jonathan Larson, Marah Ihab Abdin, Piali Choudhury, Weiwei Yang, Christopher W. White
Distance-based positive and unlabeled learning for ranking. Pattern Recognit. 134 (2023)
Hayden S. Helm, Weiwei Yang, Ashwin De Silva, Joshua T. Vogelstein, Carey E. Priebe
Approximately optimal domain adaptation with Fisher's Linear Discriminant Analysis. CoRR (2023)
Itzy E. Morales Pantoja, Lena Smirnova, Alysson R. Muotri, Karl J. Wahlin, Jeffrey Kahn, J. Lomax Boyd, David H. Gracias, Timothy D. Harris, Tzahi Cohen-Karni, Brain S. Caffo, Alexander S. Szalay, Fang Han, Donald J. Zack, Ralph Etienne-Cummings, Akwasi Akwaboah, July Carolina Romero, Dowlette-Mary Alam El Din, Jesse D. Plotkin, Barton L. Paulhamus, Erik C. Johnson, Frederic Gilbert, J. Lowry Curley, Ben Cappiello, Jens C. Schwamborn, Eric J. Hill, Paul Roach, Daniel Tornero, Caroline Krall, Rheinallt Parri, Fenna Sillé, Andre Levchenko, Rabih E. Jabbour, Brett J. Kagan, Cynthia A. Berlinicke, Qi Huang, Alexandra Maertens, Kathrin Herrmann, Katya Tsaioun, Raha M. Dastgheyb, Christa Whelan Habela, Joshua T. Vogelstein, Thomas Hartung
First Organoid Intelligence (OI) workshop to form an OI community. Frontiers Artif. Intell. 6 (2023)
Qingyang Wang, Michael Alan Powell, Eric W. Bridgeford, Ali Geisa, Joshua T. Vogelstein
Polarity Is All You Need to Learn and Transfer Faster. ICML (2023)
Adam Li, Ronan Perry, Chester Huynh, Tyler M. Tomita, Ronak Mehta, Jesús Arroyo, Jesse Patsolic, Benjamin Falk, Sridevi V. Sarma, Joshua T. Vogelstein
Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks. SIAM J. Math. Data Sci. 5 (1) (2023)
Thomas L. Athey, Matthew A. Wright, Marija Pavlovic, Vikram Chandrashekhar, Karl Deisseroth, Michael I. Miller, Joshua T. Vogelstein
BrainLine: An Open Pipeline for Connectivity Analysis of Heterogeneous Whole-Brain Fluorescence Volumes. Neuroinformatics 21 (4) (2023)
Qingyang Wang, Michael A. Powell, Ali Geisa, Eric Bridgeford, Joshua T. Vogelstein
Polarity is all you need to learn and transfer faster. CoRR (2023)
Eric W. Bridgeford, Jaewon Chung, Brian Gilbert, Sambit Panda, Adam Li, Cencheng Shen, Alexandra Badea, Brian Caffo, Joshua T. Vogelstein
Learning sources of variability from high-dimensional observational studies. CoRR (2023)
Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein
Prospective Learning: Principled Extrapolation to the Future. CoLLAs (2023)
Tianyi Chen, Youngser Park, Ali Saad-Eldin, Zachary Lubberts, Avanti Athreya, Benjamin D. Pedigo, Joshua T. Vogelstein, Francesca Puppo, Gabriel A. Silva, Alysson R. Muotri, Weiwei Yang, Christopher M. White, Carey E. Priebe
Discovering a change point and piecewise linear structure in a time series of organoid networks via the iso-mirror. Appl. Netw. Sci. 8 (1) (2023)
Thomas L. Athey, Daniel Jacob Tward, Ulrich Mueller, Laurent Younes, Joshua T. Vogelstein, Michael I. Miller
Preserving Derivative Information while Transforming Neuronal Curves. CoRR (2023)
Qingyang Wang, Michael A. Powell, Ali Geisa, Eric Bridgeford, Carey E. Priebe, Joshua T. Vogelstein
Why do networks have inhibitory/negative connections? ICCV (2023)
Jayanta Dey, Ashwin De Silva, Will LeVine, Jong M. Shin, Haoyin Xu, Ali Geisa, Tiffany Chu, Leyla Isik, Joshua T. Vogelstein
Out-of-distribution Detection Using Kernel Density Polytopes. CoRR (2022)
Dhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb, Maxim Bazhenov, Douglas Blackiston, Josh C. Bongard, Andrew P. Brna, Suraj Chakravarthi Raja, Nick Cheney, Jeff Clune, Anurag Reddy Daram, Stefano Fusi, Peter Helfer, Leslie Kay, Nicholas Ketz, Zsolt Kira, Soheil Kolouri, Jeffrey L. Krichmar, Sam Kriegman, Michael Levin, Sandeep Madireddy, Santosh Manicka, Ali Marjaninejad, Bruce McNaughton, Risto Miikkulainen, Zaneta Navratilova, Tej Pandit, Alice Parker, Praveen K. Pilly, Sebastian Risi, Terrence J. Sejnowski, Andrea Soltoggio, Nicholas Soures, Andreas S. Tolias, Darío Urbina-Meléndez, Francisco J. Valero Cuevas, Gido M. van de Ven, Joshua T. Vogelstein, Felix Wang, Ron Weiss, Angel Yanguas-Gil, Xinyun Zou, Hava T. Siegelmann
Biological underpinnings for lifelong learning machines. Nat. Mach. Intell. 4 (3) (2022)
Cencheng Shen, Sambit Panda, Joshua T. Vogelstein
The Chi-Square Test of Distance Correlation. J. Comput. Graph. Stat. 31 (1) (2022)
Qingyang Wang, Michael A. Powell, Ali Geisa, Eric Bridgeford, Joshua T. Vogelstein
Why Do Networks Need Negative Weights? CoRR (2022)
Ashwin De Silva, Rahul Ramesh, Carey E. Priebe, Pratik Chaudhari, Joshua T. Vogelstein
The Value of Out-of-Distribution Data. CoRR (2022)
Jean-Baptiste Poline, David N. Kennedy, Friedrich T. Sommer, Giorgio A. Ascoli, David C. Van Essen, Adam R. Ferguson, Jeffrey S. Grethe, Michael Hawrylycz, Paul M. Thompson, Russell A. Poldrack, Satrajit S. Ghosh, David B. Keator, Thomas L. Athey, Joshua T. Vogelstein, Helen S. Mayberg, Maryann E. Martone
Is Neuroscience FAIR? A Call for Collaborative Standardisation of Neuroscience Data. Neuroinformatics 20 (2) (2022)
Joshua T. Vogelstein, Timothy Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael Platt, Lyle Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang
Prospective Learning: Back to the Future. CoRR (2022)
Jae Wook Cho, Annachiara Korchmaros, Joshua T. Vogelstein, Michael P. Milham, Ting Xu
Impact of concatenating fMRI data on reliability for functional connectomics. NeuroImage 226 (2021)
Thomas L. Athey, Jacopo Teneggi, Joshua T. Vogelstein, Daniel Tward, Ulrich Mueller, Michael I. Miller
Fitting Splines to Axonal Arbors Quantifies Relationship between Branch Order and Geometry. CoRR (2021)
Ruoxuan Xiong, Allison Koenecke, Michael Powell, Zhu Shen, Joshua T. Vogelstein, Susan Athey
Federated Causal Inference in Heterogeneous Observational Data. CoRR (2021)
Shangsi Wang, Jesús Arroyo, Joshua T. Vogelstein, Carey E. Priebe
Joint Embedding of Graphs. IEEE Trans. Pattern Anal. Mach. Intell. 43 (4) (2021)
Haoyin Xu, Michael Ainsworth, Yu-Chung Peng, Madi Kusmanov, Sambit Panda, Joshua T. Vogelstein
When are Deep Networks really better than Random Forests at small sample sizes? CoRR (2021)
Jonathan Larson, Tiona Zuzul, Emily Cox Pahnke, Neha Parikh Shah, Patrick Bourke, Nicholas Caurvina, Fereshteh Amini, Youngser Park, Joshua T. Vogelstein, Jeffrey Weston, Christopher M. White, Carey E. Priebe
Dynamic Silos: Modularity in intra-organizational communication networks before and during the Covid-19 pandemic. CoRR (2021)
Haoyin Xu, Jayanta Dey, Sambit Panda, Joshua T. Vogelstein
Streaming Decision Trees and Forests. CoRR (2021)
Meghana Madhyastha, Kunal Lillaney, James Browne, Joshua T. Vogelstein, Randal C. Burns
BLOCKSET (Block-Aligned Serialized Trees): Reducing Inference Latency for Tree ensemble Deployment. KDD (2021)
Ali Saad-Eldin, Benjamin D. Pedigo, Carey E. Priebe, Joshua T. Vogelstein
Graph Matching via Optimal Transport. CoRR (2021)
Guilherme França, Maria L. Rizzo, Joshua T. Vogelstein
Kernel k-Groups via Hartigan's Method. IEEE Trans. Pattern Anal. Mach. Intell. 43 (12) (2021)
Jesús Arroyo, Avanti Athreya, Joshua Cape, Guodong Chen, Carey E. Priebe, Joshua T. Vogelstein
Inference for Multiple Heterogeneous Networks with a Common Invariant Subspace. J. Mach. Learn. Res. 22 (2021)
Eric W. Bridgeford, Shangsi Wang, Zeyi Wang, Ting Xu, R. Cameron Craddock, Jayanta Dey, Gregory Kiar, William Gray-Roncal, Carlo Colantuoni, Christopher Douville, Stephanie Noble, Carey E. Priebe, Brian Caffo, Michael Milham, Xi-Nian Zuo, Joshua T. Vogelstein
Eliminating accidental deviations to minimize generalization error and maximize replicability: Applications in connectomics and genomics. PLoS Comput. Biol. 17 (9) (2021)
Ali Geisa, Ronak D. Mehta, Hayden S. Helm, Jayanta Dey, Eric Eaton, Carey E. Priebe, Joshua T. Vogelstein
Towards a theory of out-of-distribution learning. CoRR (2021)
Ronan Perry, Gavin Mischler, Richard Guo, Theo Lee, Alexander Chang, Arman Koul, Cameron Franz, Hugo Richard, Iain Carmichael, Pierre Ablin, Alexandre Gramfort, Joshua T. Vogelstein
mvlearn: Multiview Machine Learning in Python. J. Mach. Learn. Res. 22 (2021)
Thomas L. Athey, Jacopo Teneggi, Joshua T. Vogelstein, Daniel Jacob Tward, Ulrich Mueller, Michael I. Miller
Fitting Splines to Axonal Arbors Quantifies Relationship Between Branch Order and Geometry. Frontiers Neuroinformatics 15 (2021)
Meghana Madhyastha, Kunal Lillaney, James Browne, Joshua T. Vogelstein, Randal C. Burns
PACSET (Packed Serialized Trees): Reducing Inference Latency for Tree Ensemble Deployment. CoRR (2020)
Karl-Heinz Nenning, Ting Xu, Ernst Schwartz, Jesús Arroyo, Adelheid Woehrer, Alexandre R. Franco, Joshua T. Vogelstein, Daniel S. Margulies, Hesheng Liu, Jonathan Smallwood, Michael P. Milham, Georg Langs
Joint embedding: A scalable alignment to compare individuals in a connectivity space. NeuroImage 222 (2020)
Meghana Madhyastha, Gongkai Li, Veronika Strnadová-Neeley, James Browne, Joshua T. Vogelstein, Randal C. Burns, Carey E. Priebe
Geodesic Forests. KDD (2020)
Ronan Perry, Gavin Mischler, Richard Guo, Theo Lee, Alexander Chang, Arman Koul, Cameron Franz, Joshua T. Vogelstein
mvlearn: Multiview Machine Learning in Python. CoRR (2020)
Joshua T. Vogelstein, Hayden S. Helm, Ronak D. Mehta, Jayanta Dey, Weiwei Yang, Bryan Tower, Will LeVine, Jonathan Larson, Christopher M. White, Carey E. Priebe
A general approach to progressive intelligence. CoRR (2020)
Hayden S. Helm, Ronak D. Mehta, Brandon Duderstadt, Weiwei Yang, Christopher M. White, Ali Geisa, Joshua T. Vogelstein, Carey E. Priebe
A partition-based similarity for classification distributions. CoRR (2020)
Tyler M. Tomita, James Browne, Cencheng Shen, Jaewon Chung, Jesse Patsolic, Benjamin Falk, Carey E. Priebe, Jason Yim, Randal C. Burns, Mauro Maggioni, Joshua T. Vogelstein
Sparse Projection Oblique Randomer Forests. J. Mach. Learn. Res. 21 (2020)
Tyler M. Tomita, Joshua T. Vogelstein
Robust Similarity and Distance Learning via Decision Forests. CoRR (2020)
Hayden S. Helm, Amitabh Basu, Avanti Athreya, Youngser Park, Joshua T. Vogelstein, Michael Winding, Marta Zlatic, Albert Cardona, Patrick Bourke, Jonathan Larson, Christopher M. White, Carey E. Priebe
Learning to rank via combining representations. CoRR (2020)
Polina Golland, Jack Gallant, Greg Hager, Hanspeter Pfister, Christos Papadimitriou, Stefan Schaal, Joshua T. Vogelstein
A New Age of Computing and the Brain. CoRR (2020)
Ting Xu, Karl-Heinz Nenning, Ernst Schwartz, Seok-Jun Hong, Joshua T. Vogelstein, Alexandros Goulas, Damien A. Fair, Charles E. Schroeder, Daniel S. Margulies, Jonny Smallwood, Michael P. Milham, Georg Langs
Cross-species functional alignment reveals evolutionary hierarchy within the connectome. NeuroImage 223 (2020)
Seok-Jun Hong, Ting Xu, Aki Nikolaidis, Jonathan Smallwood, Daniel S. Margulies, Boris C. Bernhardt, Joshua T. Vogelstein, Michael P. Milham
Toward a connectivity gradient-based framework for reproducible biomarker discovery. NeuroImage 223 (2020)
Aki Nikolaidis, Anibal Solon Heinsfeld, Ting Xu, Pierre C. Bellec, Joshua T. Vogelstein, Michael P. Milham
Bagging improves reproducibility of functional parcellation of the human brain. NeuroImage 214 (2020)
Nian Wang, Robert J. Anderson, David G. Ashbrook, Vivek Gopalakrishnan, Youngser Park, Carey E. Priebe, Yi Qi, Rick Laoprasert, Joshua T. Vogelstein, Robert W. Williams, G. Allan Johnson
Variability and heritability of mouse brain structure: Microscopic MRI atlases and connectomes for diverse strains. NeuroImage 222 (2020)
Ronak D. Mehta, Cencheng Shen, Ting Xu, Joshua T. Vogelstein
A Consistent Independence Test for Multivariate Time-Series. CoRR (2019)
Meghana Madhyastha, Percy Li, James Browne, Veronika Strnadová-Neeley, Carey E. Priebe, Randal C. Burns, Joshua T. Vogelstein
Geodesic Learning via Unsupervised Decision Forests. CoRR (2019)
Jake J. Son, Jon Clucas, Curt White, Anirudh Krishnakumar, Joshua T. Vogelstein, Michael P. Milham, Arno Klein
Thermal sensors improve wrist-worn position tracking. npj Digit. Medicine 2 (2019)
James Browne, Disa Mhembere, Tyler M. Tomita, Joshua T. Vogelstein, Randal C. Burns
Forest Packing: Fast Parallel, Decision Forests. SDM (2019)
Cencheng Shen, Joshua T. Vogelstein
The Chi-Square Test of Distance Correlation. CoRR (2019)
Runze Tang, Michael D. Ketcha, Alexandra Badea, Evan D. Calabrese, Daniel S. Margulies, Joshua T. Vogelstein, Carey E. Priebe, Daniel L. Sussman
Connectome Smoothing via Low-Rank Approximations. IEEE Trans. Medical Imaging 38 (6) (2019)
Hayden S. Helm, Joshua T. Vogelstein, Carey E. Priebe
Vertex Classification on Weighted Networks. CoRR (2019)
Jaewon Chung, Benjamin D. Pedigo, Eric W. Bridgeford, Bijan K. Varjavand, Hayden S. Helm, Joshua T. Vogelstein
GraSPy: Graph Statistics in Python. J. Mach. Learn. Res. 20 (2019)
Jaewon Chung, Benjamin D. Pedigo, Eric W. Bridgeford, Bijan K. Varjavand, Joshua T. Vogelstein
GraSPy: Graph Statistics in Python. CoRR (2019)
Richard Guo, Cencheng Shen, Joshua T. Vogelstein
Estimating Information-Theoretic Quantities with Random Forests. CoRR (2019)
Thomas L. Athey, Joshua T. Vogelstein
AutoGMM: Automatic Gaussian Mixture Modeling in Python. CoRR (2019)
Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal C. Burns
Graphyti: A Semi-External Memory Graph Library for FlashGraph. CoRR (2019)
Sambit Panda, Satish Palaniappan, Junhao Xiong, Ananya Swaminathan, Sandhya Ramachandran, Eric W. Bridgeford, Cencheng Shen, Joshua T. Vogelstein
mgcpy: A Comprehensive High Dimensional Independence Testing Python Package. CoRR (2019)
Ronan Perry, Tyler M. Tomita, Jesse Patsolic, Benjamin Falk, Joshua T. Vogelstein
Manifold Forests: Closing the Gap on Neural Networks. CoRR (2019)
Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal C. Burns
clusterNOR: A NUMA-Optimized Clustering Framework. CoRR (2019)
Jesús Arroyo, Avanti Athreya, Joshua Cape, Guodong Chen, Carey E. Priebe, Joshua T. Vogelstein
Inference for multiple heterogeneous networks with a common invariant subspace. CoRR (2019)
Cencheng Shen, Carey E. Priebe, Joshua T. Vogelstein
The Exact Equivalence of Independence Testing and Two-Sample Testing. CoRR (2019)
Da Zheng, Disa Mhembere, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns
FlashR: parallelize and scale R for machine learning using SSDs. PPOPP (2018)
Carey E. Priebe, Youngser Park, Joshua T. Vogelstein, John M. Conroy, Vince Lyzinski, Minh Tang, Avanti Athreya, Joshua Cape, Eric Bridgeford
On a 'Two Truths' Phenomenon in Spectral Graph Clustering. CoRR (2018)
James Browne, Tyler M. Tomita, Disa Mhembere, Randal C. Burns, Joshua T. Vogelstein
Forest Packing: Fast, Parallel Decision Forests. CoRR (2018)
Cencheng Shen, Joshua T. Vogelstein
Decision Forests Induce Characteristic Kernels. CoRR (2018)
Cencheng Shen, Joshua T. Vogelstein
The Exact Equivalence of Distance and Kernel Methods for Hypothesis Testing. CoRR (2018)
Kunal Lillaney, Dean Kleissas, Alexander Eusman, Eric A. Perlman, William R. Gray Roncal, Joshua T. Vogelstein, Randal C. Burns
Building NDStore Through Hierarchical Storage Management and Microservice Processing. eScience (2018)
Shangsi Wang, Joshua T. Vogelstein, Carey E. Priebe
Joint Embedding of Graphs. CoRR (2017)
Anish K. Simhal, Cecilia Aguerrebere, Forrest Collman, Joshua T. Vogelstein, Kristina D. Micheva, Richard J. Weinberg, Stephen J. Smith, Guillermo Sapiro
Probabilistic fluorescence-based synapse detection. PLoS Comput. Biol. 13 (4) (2017)
Shaojie Chen, Kai Liu, Yuguang Yang, Yuting Xu, Seonjoo Lee, Martin A. Lindquist, Brian S. Caffo, Joshua T. Vogelstein
An M-estimator for reduced-rank system identification. Pattern Recognit. Lett. 86 (2017)
Tyler M. Tomita, Mauro Maggioni, Joshua T. Vogelstein
ROFLMAO: Robust Oblique Forests with Linear MAtrix Operations. SDM (2017)
Kwame S. Kutten, Nicolas Charon, Michael I. Miller, J. Tilak Ratnanather, Jordan Matelsky, Alexander D. Baden, Kunal Lillaney, Karl Deisseroth, Li Ye, Joshua T. Vogelstein
A Large Deformation Diffeomorphic Approach to Registration of CLARITY Images via Mutual Information. MICCAI (1) (2017)
Da Zheng, Disa Mhembere, Vince Lyzinski, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns
Semi-External Memory Sparse Matrix Multiplication for Billion-Node Graphs. IEEE Trans. Parallel Distributed Syst. 28 (5) (2017)
Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal C. Burns
knor: A NUMA-Optimized In-Memory, Distributed and Semi-External-Memory k-means Library. HPDC (2017)
Cencheng Shen, Joshua T. Vogelstein, Carey E. Priebe
Manifold matching using shortest-path distance and joint neighborhood selection. Pattern Recognit. Lett. 92 (2017)
David Grant Colburn Hildebrand, Marcelo Cicconet, Russel Miguel Torres, Woohyuk Choi, Tran Minh Quan, Jungmin Moon, Arthur W. Wetzel, Andrew Scott Champion, Brett J. Graham, Owen Randlett, George S. Plummer, Ruben Portugues, Isaac Henry Bianco, Stephan Saalfeld, Alexander D. Baden, Kunal Lillaney, Randal C. Burns, Joshua T. Vogelstein, Alexander Schier, Wei-Chung Allen Lee, Won-Ki Jeong, Jeff William Lichtman, Florian Engert
Whole-brain serial-section electron microscopy in larval zebrafish. Nat. 545 (7654) (2017)
Guilherme França, Joshua T. Vogelstein
Energy Clustering. CoRR (2017)
Avanti Athreya, Donniell E. Fishkind, Minh Tang, Carey E. Priebe, Youngser Park, Joshua T. Vogelstein, Keith D. Levin, Vince Lyzinski, Yichen Qin, Daniel L. Sussman
Statistical Inference on Random Dot Product Graphs: a Survey. J. Mach. Learn. Res. 18 (2017)
Danai Koutra, Neil Shah, Joshua T. Vogelstein, Brian Gallagher, Christos Faloutsos
DeltaCon: Principled Massive-Graph Similarity Function with Attribution. ACM Trans. Knowl. Discov. Data 10 (3) (2016)
Disa Mhembere, Da Zheng, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns
NUMA-optimized In-memory and Semi-external-memory Parameterized Clustering. CoRR (2016)
Da Zheng, Disa Mhembere, Vince Lyzinski, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns
Semi-External Memory Sparse Matrix Multiplication on Billion-node Graphs in a Multicore Architecture. CoRR (2016)
Da Zheng, Disa Mhembere, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns
FlashMatrix: Parallel, Scalable Data Analysis with Generalized Matrix Operations using Commodity SSDs. CoRR (2016)
Eva L. Dyer, William R. Gray Roncal, Hugo L. Fernandes, Doga Gürsoy, Xianghui Xiao, Joshua T. Vogelstein, Chris Jacobsen, Konrad P. Körding, Narayanan Kasthuri
Quantifying mesoscale neuroanatomy using X-ray microtomography. CoRR (2016)
Li Chen, Cencheng Shen, Joshua T. Vogelstein, Carey E. Priebe
Robust Vertex Classification. IEEE Trans. Pattern Anal. Mach. Intell. 38 (3) (2016)
Anish K. Simhal, Cecilia Aguerrebere, Forrest Collman, Joshua T. Vogelstein, Kristina D. Micheva, Richard J. Weinberg, Stephen J. Smith, Guillermo Sapiro
Probabilistic Fluorescence-Based Synapse Detection. CoRR (2016)
Kwame S. Kutten, Joshua T. Vogelstein, Nicolas Charon, Li Ye, Karl Deisseroth, Michael I. Miller
Deformably Registering and Annotating Whole CLARITY Brains to an Atlas via Masked LDDMM. CoRR (2016)
Da Zheng, Randal C. Burns, Joshua T. Vogelstein, Carey E. Priebe, Alexander S. Szalay
An SSD-based eigensolver for spectral analysis on billion-node graphs. CoRR (2016)
Kwame S. Kutten, Nicolas Charon, Michael I. Miller, J. Tilak Ratnanather, Karl Deisseroth, Li Ye, Joshua T. Vogelstein
A Diffeomorphic Approach to Multimodal Registration with Mutual Information: Applications to CLARITY Mouse Brain Images. CoRR (2016)
Vince Lyzinski, Donniell E. Fishkind, Marcelo Fiori, Joshua T. Vogelstein, Carey E. Priebe, Guillermo Sapiro
Graph Matching: Relax at Your Own Risk. IEEE Trans. Pattern Anal. Mach. Intell. 38 (1) (2016)
Da Zheng, Disa Mhembere, Randal C. Burns, Joshua T. Vogelstein, Carey E. Priebe, Alexander S. Szalay
FlashGraph: Processing Billion-Node Graphs on an Array of Commodity SSDs. FAST (2015)
Vince Lyzinski, Daniel L. Sussman, Donniell E. Fishkind, Henry Pao, Li Chen, Joshua T. Vogelstein, Youngser Park, Carey E. Priebe
Spectral clustering for divide-and-conquer graph matching. Parallel Comput. 47 (2015)

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Joshua T. Vogelstein