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ORCIDTimothy Doster
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2020 – today
- 2024
[c17]James Koch, Brenda Forland, Bruce Bernacki, Timothy Doster, Tegan Emerson:
Data-Driven Invertible Neural Surrogates of Atmospheric Transmission. IGARSS 2024: 6943-6947- [i12]James Koch, Brenda Forland, Bruce Bernacki, Timothy Doster, Tegan Emerson:
Data-Driven Invertible Neural Surrogates of Atmospheric Transmission. CoRR abs/2404.19605 (2024) - [i11]Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli
, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree P. Vadgama, Erik J. Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K. Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson, Nikos Kanakaris, Boshko Koloski, Veljko Kovac, Manuel Lecha, Minho Lee, Pierrick Leroy, Theodore Long, German Magai, Alvaro Martinez, Marissa Masden, Sebastian Meznar, Bertran Miquel-Oliver, Alexis Molina, Alexander Nikitin, Marco Nurisso, Matt Piekenbrock, Yu Qin, Patryk Rygiel, Alessandro Salatiello, Max Schattauer, Pavel Snopov, Julian Suk, Valentina Sánchez, Mauricio Tec, Francesco Vaccarino, Jonas Verhellen, Frédéric Wantiez, Alexander Weers, Patrik Zajec, Blaz Skrlj, Nina Miolane:
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain. CoRR abs/2409.05211 (2024) - [i10]Ethan King, Jaime Rodriguez, Diego Llanes, Timothy Doster, Tegan Emerson, James Koch:
STARS: Sensor-agnostic Transformer Architecture for Remote Sensing. CoRR abs/2411.05714 (2024) - 2023
- [c16]Charles Godfrey, Henry Kvinge, Elise Bishoff, Myles Mckay, Davis Brown, Tim Doster, Eleanor Byler:
How many dimensions are required to find an adversarial example? CVPR Workshops 2023: 2353-2360 - [c15]Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn:
Preface. TAG-ML 2023: 1-2 - [c14]Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane:
ICML 2023 Topological Deep Learning Challenge: Design and Results. TAG-ML 2023: 3-8 - [e2]Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn:
Topological, Algebraic and Geometric Learning Workshops 2023, 28 July 2023, Honolulu, HI, USA. Proceedings of Machine Learning Research 221, PMLR 2023 [contents] - [i9]Charles Godfrey, Henry Kvinge, Elise Bishoff, Myles Mckay, Davis Brown, Tim Doster, Eleanor Byler:
How many dimensions are required to find an adversarial example? CoRR abs/2303.14173 (2023) - [i8]Michael G. Rawson, Timothy Doster, Tegan Emerson:
Reproducing Kernel Hilbert Space Pruning for Sparse Hyperspectral Abundance Prediction. CoRR abs/2308.08653 (2023) - [i7]Mathilde Papillon, Mustafa Hajij, Florian Frantzen, Josef Hoppe, Helen Jenne, Johan Mathe, Audun Myers, Theodore Papamarkou, Michael T. Schaub, Ghada Zamzmi, Tolga Birdal, Tamal K. Dey, Tim Doster, Tegan Emerson, Gurusankar Gopalakrishnan, Devendra Govil, Vincent P. Grande, Aldo Guzmán-Sáenz, Henry Kvinge, Neal Livesay, Jan Meissner, Soham Mukherjee, Shreyas N. Samaga, Karthikeyan Natesan Ramamurthy, Maneel Reddy Karri, Paul Rosen, Sophia Sanborn, Michael Scholkemper, Robin Walters, Jens Agerberg, Georg Bökman, Sadrodin Barikbin, Claudio Battiloro, Gleb Bazhenov, Guillermo Bernárdez, Aiden Brent, Sergio Escalera, Simone Fiorellino, Dmitrii Gavrilev, Mohammed Hassanin, Paul Häusner, Odin Hoff Gardaa, Abdelwahed Khamis, Manuel Lecha, German Magai, Tatiana Malygina, Pavlo Melnyk, et al.:
ICML 2023 Topological Deep Learning Challenge : Design and Results. CoRR abs/2309.15188 (2023) - 2022
- [c13]Henry Kvinge, Tegan Emerson, Grayson Jorgenson, Scott Vasquez, Tim Doster, Jesse D. Lew:
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? NeurIPS 2022 - [c12]Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf:
Preface. TAG-ML 2022: 1-5 - [e1]Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf:
Topological, Algebraic and Geometric Learning Workshops 2022, 25-22 July 2022, Virtual. Proceedings of Machine Learning Research 196, PMLR 2022 [contents] - [i6]Henry Kvinge, Tegan H. Emerson, Grayson Jorgenson, Scott Vasquez, Timothy Doster, Jesse D. Lew:
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? CoRR abs/2210.03773 (2022) - 2021
- [c11]Sarah Tymochko, Julien Chaput, Timothy Doster, Emilie Purvine, Jackson Warley, Tegan Emerson:
Con Connections: Detecting Fraud from Abstracts using Topological Data Analysis. ICMLA 2021: 403-408 - [i5]Scott Mahan, Henry Kvinge, Tim Doster:
Rotating spiders and reflecting dogs: a class conditional approach to learning data augmentation distributions. CoRR abs/2106.04009 (2021) - [i4]Ted Fujimoto, Timothy Doster, Adam Attarian, Jill Brandenberger, Nathan Hodas:
Reward-Free Attacks in Multi-Agent Reinforcement Learning. CoRR abs/2112.00940 (2021) - [i3]Scott Mahan, Tim Doster, Henry Kvinge:
DNA: Dynamic Network Augmentation. CoRR abs/2112.09277 (2021) - 2020
- [j1]Tegan H. Emerson, Colin C. Olson, Timothy Doster:
Path-Based Dictionary Augmentation: A Framework for Improving k-Sparse Image Processing. IEEE Trans. Image Process. 29: 1259-1270 (2020) - [c10]Lucius Bynum, Timothy Doster, Tegan H. Emerson, Henry Kvinge:
Rotational Equivariance for Object Classification Using xView. IGARSS 2020: 3684-3687 - [i2]Sarah Tymochko, Zachary New, Lucius Bynum, Emilie Purvine, Timothy Doster, Julien Chaput, Tegan Emerson:
Argumentative Topology: Finding Loop(holes) in Logic. CoRR abs/2011.08952 (2020)
2010 – 2019
- 2019
- [c9]Tegan H. Emerson, Jason A. Edelberg, Timothy Doster, Nicholas Merrill, Colin C. Olson:
Generative And Encoded Anomaly Detectors. WHISPERS 2019: 1-5 - 2018
- [c8]Timothy Doster, Tegan Emerson, Colin C. Olson:
Path Orthogonal Matching Pursuit for Sparse Reconstruction and Denoising of SWIR Maritime Imagery. CVPR Workshops 2018: 1161-1168 - [c7]Tegan H. Emerson, Timothy Doster, Colin C. Olson:
Path Orthogonal Matching Pursuit for k-Sparse Image Reconstruction. EUSIPCO 2018: 1955-1959 - [c6]Tegan H. Emerson, Timothy Doster, Colin C. Olson:
Path-Based Background Model Augmentation for Hyperspectral Anomaly Detection. WHISPERS 2018: 1-5 - 2017
- [c5]Timothy Doster, Colin C. Olson, Erin Fleet, Michael Yetzbacher:
Selecting an Optimized COTS Filter Set for Multispectral Plenoptic Sensing. CVPR Workshops 2017: 293-301 - [c4]Colin C. Olson, Timothy Doster:
A Novel Detection Paradigm and Its Comparison to Statistical and Kernel-Based Anomaly Detection Algorithms for Hyperspectral Imagery. CVPR Workshops 2017: 302-308 - 2016
- [c3]Leslie N. Smith, Emily M. Hand, Timothy Doster:
Gradual DropIn of Layers to Train Very Deep Neural Networks. CVPR 2016: 4763-4771 - 2015
- [i1]Leslie N. Smith, Emily M. Hand, Timothy Doster:
Gradual DropIn of Layers to Train Very Deep Neural Networks. CoRR abs/1511.06951 (2015) - 2014
- [c2]Alexander Cloninger, Wojciech Czaja, Timothy Doster:
Operator analysis and diffusion based embeddings for heterogeneous data fusion. IGARSS 2014: 1249-1252 - 2013
- [c1]Alexander Cloninger, Wojciech Czaja, Timothy Doster:
A case study on data fusion with overlapping segments. AIPR 2013: 1-11
Coauthor Index
aka: Tegan H. Emerson
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