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Journal Articles
- 2025
[j46]Guodong Chen, Jesús Arroyo, Avanti Athreya, Joshua Cape, Joshua T. Vogelstein, Youngser Park, Christopher M. White, Jonathan Larson, Weiwei Yang, Carey E. Priebe:
Multiple network embedding for anomaly detection in time series of graphs. Comput. Stat. Data Anal. 203: 108070 (2025)- 2024
- [j45]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): 63-74 (2024) - [j44]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: 97-102 (2024) - [j43]Cencheng Shen, Jaewon Chung, Ronak D. Mehta, Ting Xu, Joshua T. Vogelstein:
Independence Testing for Temporal Data. Trans. Mach. Learn. Res. 2024 (2024) - 2023
- [j42]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): 45 (2023) - [j41]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, Brian 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) - [j40]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): 637-639 (2023) - [j39]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 M. White:
Distance-based positive and unlabeled learning for ranking. Pattern Recognit. 134: 109085 (2023) - [j38]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): 77-96 (2023) - 2022
- [j37]Cencheng Shen, Sambit Panda, Joshua T. Vogelstein:
The Chi-Square Test of Distance Correlation. J. Comput. Graph. Stat. 31(1): 254-262 (2022) - [j36]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): 196-210 (2022) - [j35]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): 507-512 (2022) - 2021
- [j34]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: 704627 (2021) - [j33]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: 109:1-109:7 (2021) - [j32]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: 142:1-142:49 (2021) - [j31]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: 117549 (2021) - [j30]Shangsi Wang, Jesús Arroyo, Joshua T. Vogelstein, Carey E. Priebe:
Joint Embedding of Graphs. IEEE Trans. Pattern Anal. Mach. Intell. 43(4): 1324-1336 (2021) - [j29]Guilherme França, Maria L. Rizzo, Joshua T. Vogelstein:
Kernel k-Groups via Hartigan's Method. IEEE Trans. Pattern Anal. Mach. Intell. 43(12): 4411-4425 (2021) - [j28]Eric W. Bridgeford, Shangsi Wang, Zeyi Wang, Ting Xu, R. Cameron Craddock, Jayanta Dey, Gregory Kiar, William R. Gray Roncal, Carlo Colantuoni, Christopher Douville, Stephanie Noble, Carey E. Priebe, Brian Caffo, Michael P. 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) - 2020
- [j27]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: 104:1-104:39 (2020) - [j26]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: 116678 (2020) - [j25]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: 117232 (2020) - [j24]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: 117274 (2020) - [j23]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: 117322 (2020) - [j22]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: 117346 (2020) - 2019
- [j21]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: 158:1-158:7 (2019) - [j20]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) - [j19]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): 1446-1456 (2019) - 2017
- [j18]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: 226:1-226:92 (2017) - [j17]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): 345-349 (2017) - [j16]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) - [j15]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: 76-81 (2017) - [j14]Cencheng Shen, Joshua T. Vogelstein, Carey E. Priebe:
Manifold matching using shortest-path distance and joint neighborhood selection. Pattern Recognit. Lett. 92: 41-48 (2017) - [j13]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): 1470-1483 (2017) - 2016
- [j12]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): 60-73 (2016) - [j11]Li Chen, Cencheng Shen, Joshua T. Vogelstein, Carey E. Priebe:
Robust Vertex Classification. IEEE Trans. Pattern Anal. Mach. Intell. 38(3): 578-590 (2016) - [j10]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): 28:1-28:43 (2016) - 2015
- [j9]Joshua T. Vogelstein, Carey E. Priebe:
Shuffled Graph Classification: Theory and Connectome Applications. J. Classif. 32(1): 3-20 (2015) - [j8]William R. Gray Roncal, Dean M. Kleissas, Joshua T. Vogelstein, Priya Manavalan, Kunal Lillaney, Michael J. Pekala, Randal C. Burns, R. Jacob Vogelstein, Carey E. Priebe, Mark A. Chevillet, Gregory D. Hager:
An Automated Images-to-Graphs Framework for High Resolution Connectomics. Frontiers Neuroinformatics 9: 20 (2015) - [j7]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: 70-87 (2015) - 2014
- [j6]David E. Carlson, Joshua T. Vogelstein, Qisong Wu, Wenzhao Lian, Mingyuan Zhou, Colin R. Stoetzner, Daryl Kipke, Douglas Weber, David B. Dunson, Lawrence Carin:
Multichannel Electrophysiological Spike Sorting via Joint Dictionary Learning and Mixture Modeling. IEEE Trans. Biomed. Eng. 61(1): 41-54 (2014) - 2013
- [j5]Dai Dai, Huiguang He, Joshua T. Vogelstein, Zengguang Hou:
Accurate prediction of AD patients using cortical thickness networks. Mach. Vis. Appl. 24(7): 1445-1457 (2013) - [j4]Joshua T. Vogelstein, William R. Gray Roncal, R. Jacob Vogelstein, Carey E. Priebe:
Graph Classification Using Signal-Subgraphs: Applications in Statistical Connectomics. IEEE Trans. Pattern Anal. Mach. Intell. 35(7): 1539-1551 (2013) - [j3]Donniell E. Fishkind, Daniel L. Sussman, Minh Tang, Joshua T. Vogelstein, Carey E. Priebe:
Consistent Adjacency-Spectral Partitioning for the Stochastic Block Model When the Model Parameters Are Unknown. SIAM J. Matrix Anal. Appl. 34(1): 23-39 (2013) - 2010
- [j2]Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreira, Shinsuke Koyama, Kamiar Rahnama Rad, Michael Vidne, Joshua T. Vogelstein, Wei Wu:
A new look at state-space models for neural data. J. Comput. Neurosci. 29(1-2): 107-126 (2010) - 2007
- [j1]R. Jacob Vogelstein, Udayan Mallik, Joshua T. Vogelstein, Gert Cauwenberghs:
Dynamically Reconfigurable Silicon Array of Spiking Neurons With Conductance-Based Synapses. IEEE Trans. Neural Networks 18(1): 253-265 (2007)
Conference and Workshop Papers
- 2024
- [c26]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: 1792-1804 - 2023
- [c25]Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael L. 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: 347-357 - [c24]Qingyang Wang, Michael A. Powell, Ali Geisa, Eric Bridgeford, Carey E. Priebe, Joshua T. Vogelstein:
Why do networks have inhibitory/negative connections? ICCV 2023: 22494-22502 - [c23]Ashwin De Silva, Rahul Ramesh, Carey E. Priebe, Pratik Chaudhari, Joshua T. Vogelstein:
The Value of Out-of-Distribution Data. ICML 2023: 7366-7389 - [c22]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: 36264-36284 - 2021
- [c21]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: 1170-1179 - 2020
- [c20]Meghana Madhyastha, Gongkai Li, Veronika Strnadová-Neeley, James Browne, Joshua T. Vogelstein, Randal C. Burns, Carey E. Priebe:
Geodesic Forests. KDD 2020: 513-523 - 2019
- [c19]James Browne, Disa Mhembere, Tyler M. Tomita, Joshua T. Vogelstein, Randal C. Burns:
Forest Packing: Fast Parallel, Decision Forests. SDM 2019: 46-54 - 2018
- [c18]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: 223-233 - [c17]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: 183-194 - 2017
- [c16]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: 67-78 - [c15]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: 275-282 - [c14]Tyler M. Tomita, Mauro Maggioni, Joshua T. Vogelstein:
ROFLMAO: Robust Oblique Forests with Linear MAtrix Operations. SDM 2017: 498-506 - 2015
- [c13]William R. Gray Roncal, Michael J. Pekala, Verena Kaynig-Fittkau, Dean M. Kleissas, Joshua T. Vogelstein, Hanspeter Pfister, Randal C. Burns, R. Jacob Vogelstein, Mark A. Chevillet, Gregory D. Hager:
VESICLE: Volumetric Evaluation of Synaptic Inferfaces using Computer Vision at Large Scale. BMVC 2015: 81.1-81.13 - [c12]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: 45-58 - 2013
- [c11]Vivek Kulkarni, Jagat Sastry Pudipeddi, Leman Akoglu, Joshua T. Vogelstein, R. Jacob Vogelstein, Sephira Ryman, Rex E. Jung:
Sex Differences in the Human Connectome. Brain and Health Informatics 2013: 82-91 - [c10]Disa Mhembere, William R. Gray Roncal, Daniel L. Sussman, Carey E. Priebe, Rex E. Jung, Sephira Ryman, R. Jacob Vogelstein, Joshua T. Vogelstein, Randal C. Burns:
Computing scalable multivariate glocal invariants of large (brain-) graphs. GlobalSIP 2013: 297-300 - [c9]William R. Gray Roncal, Zachary H. Koterba, Disa Mhembere, Dean M. Kleissas, Joshua T. Vogelstein, Randal C. Burns, Anita R. Bowles, Dimitrios K. Donavos, Sephira Ryman, Rex E. Jung, Lei Wu, Vince D. Calhoun, R. Jacob Vogelstein:
MIGRAINE: MRI Graph Reliability Analysis and Inference for Connectomics. GlobalSIP 2013: 313-316 - [c8]Bruno Cornelis, Yun Yang, Joshua T. Vogelstein, Ann Dooms, Ingrid Daubechies, David B. Dunson:
Bayesian crack detection in ultra high resolution multimodal images of paintings. DSP 2013: 1-8 - [c7]Marcelo Fiori, Pablo Sprechmann, Joshua T. Vogelstein, Pablo Musé, Guillermo Sapiro:
Robust Multimodal Graph Matching: Sparse Coding Meets Graph Matching. NIPS 2013: 127-135 - [c6]Francesca Petralia, Joshua T. Vogelstein, David B. Dunson:
Multiscale Dictionary Learning for Estimating Conditional Distributions. NIPS 2013: 1797-1805 - [c5]David E. Carlson, Vinayak A. Rao, Joshua T. Vogelstein, Lawrence Carin:
Real-Time Inference for a Gamma Process Model of Neural Spiking. NIPS 2013: 2805-2813 - [c4]Christos Faloutsos, Danai Koutra, Joshua T. Vogelstein:
DELTACON: A Principled Massive-Graph Similarity Function. SDM 2013: 162-170 - [c3]Randal C. Burns, Kunal Lillaney, Daniel R. Berger, Logan Grosenick, Karl Deisseroth, R. Clay Reid, William R. Gray Roncal, Priya Manavalan, Davi Bock, Narayanan Kasthuri, Michael M. Kazhdan, Stephen J. Smith, Dean Kleissas, Eric A. Perlman, Kwanghun Chung, Nicholas C. Weiler, Jeff Lichtman, Alexander S. Szalay, Joshua T. Vogelstein, R. Jacob Vogelstein:
The open connectome project data cluster: scalable analysis and vision for high-throughput neuroscience. SSDBM 2013: 27:1-27:11 - 2011
- [c2]Dai Dai, Huiguang He, Joshua T. Vogelstein, Zengguang Hou:
Network-Based Classification Using Cortical Thickness of AD Patients. MLMI 2011: 193-200 - 2008
- [c1]Quentin J. M. Huys, Joshua T. Vogelstein, Peter Dayan:
Psychiatry: Insights into depression through normative decision-making models. NIPS 2008: 729-736
Informal and Other Publications
- 2023
- [i64]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 abs/2302.14186 (2023) - [i63]Thomas L. Athey, Daniel Jacob Tward, Ulrich Mueller, Laurent Younes, Joshua T. Vogelstein, Michael I. Miller:
Preserving Derivative Information while Transforming Neuronal Curves. CoRR abs/2303.09649 (2023) - [i62]Qingyang Wang, Michael A. Powell, Ali Geisa, Eric Bridgeford, Joshua T. Vogelstein:
Polarity is all you need to learn and transfer faster. CoRR abs/2303.17589 (2023) - [i61]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 abs/2307.13868 (2023) - 2022
- [i60]Joshua T. Vogelstein, Timothy D. 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 L. Platt, Lyle H. 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 abs/2201.07372 (2022) - [i59]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 abs/2201.13001 (2022) - [i58]Qingyang Wang, Michael A. Powell, Ali Geisa, Eric Bridgeford, Joshua T. Vogelstein:
Why Do Networks Need Negative Weights? CoRR abs/2208.03211 (2022) - [i57]Ashwin De Silva, Rahul Ramesh, Carey E. Priebe, Pratik Chaudhari, Joshua T. Vogelstein:
The Value of Out-of-Distribution Data. CoRR abs/2208.10967 (2022) - 2021
- [i56]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 abs/2104.00641 (2021) - [i55]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 abs/2104.01532 (2021) - [i54]Ruoxuan Xiong, Allison Koenecke, Michael A. Powell, Zhu Shen, Joshua T. Vogelstein, Susan Athey:
Federated Causal Inference in Heterogeneous Observational Data. CoRR abs/2107.11732 (2021) - [i53]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 abs/2108.13637 (2021) - [i52]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 abs/2109.14501 (2021) - [i51]Haoyin Xu, Jayanta Dey, Sambit Panda, Joshua T. Vogelstein:
Streaming Decision Trees and Forests. CoRR abs/2110.08483 (2021) - [i50]Ali Saad-Eldin, Benjamin D. Pedigo, Carey E. Priebe, Joshua T. Vogelstein:
Graph Matching via Optimal Transport. CoRR abs/2111.05366 (2021) - 2020
- [i49]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 abs/2004.12908 (2020) - [i48]Polina Golland, Jack L. Gallant, Greg Hager, Hanspeter Pfister, Christos H. Papadimitriou, Stefan Schaal, Joshua T. Vogelstein:
A New Age of Computing and the Brain. CoRR abs/2004.12926 (2020) - [i47]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 abs/2005.10700 (2020) - [i46]Ronan Perry, Gavin Mischler, Richard Guo, Theo Lee, Alexander Chang, Arman Koul, Cameron Franz, Joshua T. Vogelstein:
mvlearn: Multiview Machine Learning in Python. CoRR abs/2005.11890 (2020) - [i45]Tyler M. Tomita, Joshua T. Vogelstein:
Robust Similarity and Distance Learning via Decision Forests. CoRR abs/2007.13843 (2020) - [i44]Meghana Madhyastha, Kunal Lillaney, James Browne, Joshua T. Vogelstein, Randal C. Burns:
PACSET (Packed Serialized Trees): Reducing Inference Latency for Tree Ensemble Deployment. CoRR abs/2011.05383 (2020) - [i43]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 abs/2011.06557 (2020) - 2019
- [i42]Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal C. Burns:
clusterNOR: A NUMA-Optimized Clustering Framework. CoRR abs/1902.09527 (2019) - [i41]Jaewon Chung, Benjamin D. Pedigo, Eric W. Bridgeford, Bijan K. Varjavand, Joshua T. Vogelstein:
GraSPy: Graph Statistics in Python. CoRR abs/1904.05329 (2019) - [i40]Hayden S. Helm, Joshua T. Vogelstein, Carey E. Priebe:
Vertex Classification on Weighted Networks. CoRR abs/1906.02881 (2019) - [i39]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 abs/1906.10026 (2019) - [i38]Richard Guo, Cencheng Shen, Joshua T. Vogelstein:
Estimating Information-Theoretic Quantities with Random Forests. CoRR abs/1907.00325 (2019) - [i37]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 abs/1907.02088 (2019) - [i36]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 abs/1907.02844 (2019) - [i35]Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal C. Burns:
Graphyti: A Semi-External Memory Graph Library for FlashGraph. CoRR abs/1907.03335 (2019) - [i34]Ronak D. Mehta, Cencheng Shen, Ting Xu, Joshua T. Vogelstein:
A Consistent Independence Test for Multivariate Time-Series. CoRR abs/1908.06486 (2019) - [i33]Thomas L. Athey, Joshua T. Vogelstein:
AutoGMM: Automatic Gaussian Mixture Modeling in Python. CoRR abs/1909.02688 (2019) - [i32]Ronan Perry, Tyler M. Tomita, Jesse Patsolic, Benjamin Falk, Joshua T. Vogelstein:
Manifold Forests: Closing the Gap on Neural Networks. CoRR abs/1909.11799 (2019) - [i31]Cencheng Shen, Carey E. Priebe, Joshua T. Vogelstein:
The Exact Equivalence of Independence Testing and Two-Sample Testing. CoRR abs/1910.08883 (2019) - [i30]Cencheng Shen, Joshua T. Vogelstein:
The Chi-Square Test of Distance Correlation. CoRR abs/1912.12150 (2019) - 2018
- [i29]Cencheng Shen, Joshua T. Vogelstein:
The Exact Equivalence of Distance and Kernel Methods for Hypothesis Testing. CoRR abs/1806.05514 (2018) - [i28]James Browne, Tyler M. Tomita, Disa Mhembere, Randal C. Burns, Joshua T. Vogelstein:
Forest Packing: Fast, Parallel Decision Forests. CoRR abs/1806.07300 (2018) - [i27]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 abs/1808.07801 (2018) - [i26]Cencheng Shen, Joshua T. Vogelstein:
Decision Forests Induce Characteristic Kernels. CoRR abs/1812.00029 (2018) - 2017
- [i25]Shangsi Wang, Joshua T. Vogelstein, Carey E. Priebe:
Joint Embedding of Graphs. CoRR abs/1703.03862 (2017) - [i24]Guilherme França, Joshua T. Vogelstein:
Energy Clustering. CoRR abs/1710.09859 (2017) - 2016
- [i23]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 abs/1602.01421 (2016) - [i22]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 abs/1602.02864 (2016) - [i21]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 abs/1604.03629 (2016) - [i20]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 abs/1604.06414 (2016) - [i19]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 abs/1605.02060 (2016) - [i18]Disa Mhembere, Da Zheng, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns:
NUMA-optimized In-memory and Semi-external-memory Parameterized Clustering. CoRR abs/1606.08905 (2016) - [i17]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 abs/1611.05479 (2016) - [i16]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 abs/1612.00356 (2016) - 2015
- [i15]Michael M. Kazhdan, Kunal Lillaney, William R. Gray Roncal, Davi Bock, Joshua T. Vogelstein, Randal C. Burns:
Gradient-Domain Fusion for Color Correction in Large EM Image Stacks. CoRR abs/1506.02079 (2015) - [i14]Tyler M. Tomita, Mauro Maggioni, Joshua T. Vogelstein:
Randomer Forests. CoRR abs/1506.03410 (2015) - 2014
- [i13]William R. Gray Roncal, Verena Kaynig-Fittkau, Narayanan Kasthuri, Daniel R. Berger, Joshua T. Vogelstein, Lindsey R. Fernandez, Jeff W. Lichtman, R. Jacob Vogelstein, Hanspeter Pfister, Gregory D. Hager:
Volumetric Exploitation of Synaptic Information using Context Localization and Evaluation. CoRR abs/1403.3724 (2014) - [i12]Ayushi Sinha, William R. Gray Roncal, Narayanan Kasthuri, Ming Chuang, Priya Manavalan, Dean Kleissas, Joshua T. Vogelstein, R. Jacob Vogelstein, Randal C. Burns, Jeff W. Lichtman, Michael M. Kazhdan:
Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes. CoRR abs/1404.4800 (2014) - [i11]Norbert Binkiewicz, Joshua T. Vogelstein, Karl Rohe:
Covariate Assisted Spectral Clustering. CoRR abs/1411.2158 (2014) - [i10]William R. Gray Roncal, Dean Kleissas, Joshua T. Vogelstein, Priya Manavalan, Randal C. Burns, R. Jacob Vogelstein, Carey E. Priebe, Mark A. Chevillet, Gregory D. Hager:
An Automated Images-to-Graphs Pipeline for High Resolution Connectomics. CoRR abs/1411.6880 (2014) - 2013
- [i9]Danai Koutra, Joshua T. Vogelstein, Christos Faloutsos:
DELTACON: A Principled Massive-Graph Similarity Function. CoRR abs/1304.4657 (2013) - [i8]Bruno Cornelis, Yun Yang, Joshua T. Vogelstein, Ann Dooms, Ingrid Daubechies, David B. Dunson:
Bayesian crack detection in ultra high resolution multimodal images of paintings. CoRR abs/1304.5894 (2013) - [i7]Randal C. Burns, William R. Gray Roncal, Dean Kleissas, Kunal Lillaney, Priya Manavalan, Eric A. Perlman, Daniel R. Berger, Davi Bock, Kwanghun Chung, Logan Grosenick, Narayanan Kasthuri, Nicholas C. Weiler, Karl Deisseroth, Michael M. Kazhdan, Jeff Lichtman, R. Clay Reid, Stephen J. Smith, Alexander S. Szalay, Joshua T. Vogelstein, R. Jacob Vogelstein:
The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience. CoRR abs/1306.3543 (2013) - [i6]Michael M. Kazhdan, Randal C. Burns, Bobby Kasthuri, Jeff Lichtman, R. Jacob Vogelstein, Joshua T. Vogelstein:
Gradient-Domain Processing for Large EM Image Stacks. CoRR abs/1310.0041 (2013) - [i5]Marcelo Fiori, Pablo Sprechmann, Joshua T. Vogelstein, Pablo Musé, Guillermo Sapiro:
Robust Multimodal Graph Matching: Sparse Coding Meets Graph Matching. CoRR abs/1311.6425 (2013) - [i4]Francesca Petralia, Joshua T. Vogelstein, David B. Dunson:
Multiscale Dictionary Learning for Estimating Conditional Distributions. CoRR abs/1312.1099 (2013) - [i3]Disa Mhembere, William R. Gray Roncal, Daniel L. Sussman, Carey E. Priebe, Rex E. Jung, Sephira Ryman, R. Jacob Vogelstein, Joshua T. Vogelstein, Randal C. Burns:
Computing Scalable Multivariate Glocal Invariants of Large (Brain-) Graphs. CoRR abs/1312.4318 (2013) - [i2]William R. Gray Roncal, Zachary H. Koterba, Disa Mhembere, Dean Kleissas, Joshua T. Vogelstein, Randal C. Burns, Anita R. Bowles, Dimitrios K. Donavos, Sephira Ryman, Rex E. Jung, Lei Wu, Vince D. Calhoun, R. Jacob Vogelstein:
MIGRAINE: MRI Graph Reliability Analysis and Inference for Connectomics. CoRR abs/1312.4875 (2013) - 2011
- [i1]Joshua T. Vogelstein, John M. Conroy, Louis J. Podrazik, Steven G. Kratzer, Donniell E. Fishkind, R. Jacob Vogelstein, Carey E. Priebe:
Fast Inexact Graph Matching with Applications in Statistical Connectomics. CoRR abs/1112.5507 (2011)
Coauthor Index
[j46] [j44] [j42] [j39] [j32] [j30] [j28] [j27] [j24] [j19] [j18] [j14] [j13] [j12] [j11] [j9] [j8] [j7] [j4] [j3] [c25] [c24] [c23] [c20] [c17] [c16] [c12] [c10] [i64] [i60] [i57] [i56] [i52] [i50] [i49] [i47] [i43] [i42] [i40] [i39] [i36] [i35] [i31] [i27] [i25] [i23] [i22] [i20] [i18] [i10] [i3] [i1]
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