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Nathan Drenkow
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2020 – today
- 2024
- [c13]Nathan Drenkow, Mathias Unberath:
RobustCLEVR: A Benchmark and Framework for Evaluating Robustness in Object-centric Learning. WACV 2024: 4506-4515 - [i12]Kanyifeechukwu Jane Oguine, Roger D. Soberanis-Mukul, Nathan Drenkow, Mathias Unberath:
From Generalization to Precision: Exploring SAM for Tool Segmentation in Surgical Environments. CoRR abs/2402.17972 (2024) - [i11]Nathan Drenkow, Chris Ribaudo, Mathias Unberath:
Causality-Driven Audits of Model Robustness. CoRR abs/2410.23494 (2024) - 2023
- [c12]Mitchell Pavlak, Nathan Drenkow, Nicholas Petrick, Mohammad Mehdi Farhangi, Mathias Unberath:
Data AUDIT: Identifying Attribute Utility- and Detectability-Induced Bias in Task Models. MICCAI (3) 2023: 442-452 - [c11]Brian S. Robinson, Nathan Drenkow, Colin Conwell, Michael F. Bonner:
A sparse null code emerges in deep neural networks. UniReps 2023: 302-314 - [c10]Nathan Drenkow, Max Lennon, I-Jeng Wang, Philippe Burlina:
Do Adaptive Active Attacks Pose Greater Risk Than Static Attacks? WACV 2023: 1380-1389 - [i10]Mitchell Pavlak, Nathan Drenkow, Nicholas Petrick, Mohammad Mehdi Farhangi, Mathias Unberath:
Data AUDIT: Identifying Attribute Utility- and Detectability-Induced Bias in Task Models. CoRR abs/2304.03218 (2023) - [i9]Erik C. Johnson, Brian S. Robinson, Gautam K. Vallabha, Justin Joyce, Jordan K. Matelsky, Raphael Norman-Tenazas, Isaac Western, Marisel Villafañe-Delgado, Martha Cervantes, Michael S. Robinette, Arun V. Reddy, Lindsey Kitchell, Patricia K. Rivlin, Elizabeth Perez Reilly, Nathan Drenkow, Matthew J. Roos, I-Jeng Wang, Brock A. Wester, William R. Gray Roncal, Joan A. Hoffmann:
Exploiting Large Neuroimaging Datasets to Create Connectome-Constrained Approaches for more Robust, Efficient, and Adaptable Artificial Intelligence. CoRR abs/2305.17300 (2023) - [i8]Nathan Drenkow, Mathias Unberath:
RobustCLEVR: A Benchmark and Framework for Evaluating Robustness in Object-centric Learning. CoRR abs/2308.14899 (2023) - 2022
- [c9]Nathan Drenkow, Neil Fendley, Philippe Burlina:
Attack Agnostic Detection of Adversarial Examples via Random Subspace Analysis. WACV 2022: 2815-2825 - [i7]Nathan Drenkow, Alvin Tan, Chace Ashcraft, Kiran Karra:
Context-Adaptive Deep Neural Networks via Bridge-Mode Connectivity. CoRR abs/2211.15436 (2022) - 2021
- [c8]Nathan Drenkow, Philippe Burlina, Neil Fendley, Onyekachi Odoemene, Jared Markowitz:
Addressing Visual Search in Open and Closed Set Settings. CVPR Workshops 2021: 1143-1151 - [c7]Zhaoshuo Li, Xingtong Liu
, Nathan Drenkow, Andy S. Ding, Francis X. Creighton, Russell H. Taylor, Mathias Unberath:
Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers. ICCV 2021: 6177-6186 - [c6]Max Lennon, Nathan Drenkow, Philippe Burlina:
Patch Attack Invariance: How Sensitive are Patch Attacks to 3D Pose? ICCVW 2021: 112-121 - [i6]Max Lennon, Nathan Drenkow, Philippe Burlina:
Patch Attack Invariance: How Sensitive are Patch Attacks to 3D Pose? CoRR abs/2108.07229 (2021) - [i5]Zhaoshuo Li, Nathan Drenkow, Hao Ding, Andy S. Ding, Alexander Lu, Francis X. Creighton, Russell H. Taylor, Mathias Unberath:
On the Sins of Image Synthesis Loss for Self-supervised Depth Estimation. CoRR abs/2109.06163 (2021) - [i4]Nathan Drenkow, Numair Sani, Ilya Shpitser, Mathias Unberath:
Robustness in Deep Learning for Computer Vision: Mind the gap? CoRR abs/2112.00639 (2021) - 2020
- [c5]Neil Fendley, Max Lennon, I-Jeng Wang, Philippe Burlina, Nathan Drenkow:
Jacks of All Trades, Masters of None: Addressing Distributional Shift and Obtrusiveness via Transparent Patch Attacks. ECCV Workshops (1) 2020: 105-119 - [c4]Nathan Drenkow, Justin Joyce
Leveraging Tools from Autonomous Navigation for Rapid, Robust Neuron Connectivity. MICCAI (5) 2020: 109-118 - [i3]Neil Fendley, Max Lennon, I-Jeng Wang, Philippe Burlina, Nathan Drenkow:
Jacks of All Trades, Masters Of None: Addressing Distributional Shift and Obtrusiveness via Transparent Patch Attacks. CoRR abs/2005.00656 (2020) - [i2]Nathan Drenkow, Neil Fendley, Philippe Burlina:
Random Projections for Adversarial Attack Detection. CoRR abs/2012.06405 (2020) - [i1]Nathan Drenkow, Philippe Burlina, Neil Fendley, Kachi Odoemene, Jared Markowitz:
Objectness-Guided Open Set Visual Search and Closed Set Detection. CoRR abs/2012.06509 (2020)
2010 – 2019
- 2019
- [c3]Ryan W. Gardner, Corey Lowman, Casey Richardson, Ashley J. Llorens, Jared Markowitz, Nathan Drenkow, Andrew Newman, Gregory Clark, Gino Perrotta, Robert Perrotta, Timothy Highley, Vlad Shcherbina, William Bernadoni, Mark Jordan, Asen Asenov:
The First International Competition in Machine Reconnaissance Blind Chess. NeurIPS (Competition and Demos) 2019: 121-130 - 2014
- [c2]Pedro A. Rodriguez, Nathan Drenkow, Daniel DeMenthon, Zachary H. Koterba, Kathleen Kauffman, Duane Cornish, Bart L. Paulhamus, R. Jacob Vogelstein
Selection of universal features for image classification. WACV 2014: 355-362 - 2013
- [c1]Nathan Drenkow, Philippe Burlina, I-Jeng Wang, Daniel DeMenthon, Craig Carmen:
A practical test set bound for rank learning. MLSP 2013: 1-6
Coauthor Index
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