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ORCIDZachariah Carmichael
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2020 – today
- 2024
[c10]Soumyendu Sarkar, Ashwin Ramesh Babu, Sajad Mousavi, Zachariah Carmichael, Vineet Gundecha, Sahand Ghorbanpour, Ricardo Luna Gutierrez, Antonio Guillen, Avisek Naug:
Benchmark Generation Framework with Customizable Distortions for Image Classifier Robustness. WACV 2024: 4406-4415- [c9]Zachariah Carmichael, Suhas Lohit, Anoop Cherian, Michael J. Jones, Walter J. Scheirer:
Pixel-Grounded Prototypical Part Networks. WACV 2024: 4756-4767 - [i17]Zachariah Carmichael, Timothy Redgrave, Daniel Gonzalez Cedre, Walter J. Scheirer:
This Probably Looks Exactly Like That: An Invertible Prototypical Network. CoRR abs/2407.12200 (2024) - 2023
- [c8]Zachariah Carmichael, Walter J. Scheirer:
Unfooling Perturbation-Based Post Hoc Explainers. AAAI 2023: 6925-6934 - [c7]William Theisen, Daniel Gonzalez Cedre, Zachariah Carmichael, Daniel Moreira
, Tim Weninger, Walter J. Scheirer:
Motif Mining: Finding and Summarizing Remixed Image Content. WACV 2023: 1319-1328 - [i16]Sophia J. Abraham, Kehelwala D. G. Maduranga, Jeffery Kinnison, Zachariah Carmichael, Jonathan D. Hauenstein, Walter J. Scheirer:
HomOpt: A Homotopy-Based Hyperparameter Optimization Method. CoRR abs/2308.03317 (2023) - [i15]Zachariah Carmichael, Suhas Lohit, Anoop Cherian, Michael N. Jones, Walter J. Scheirer:
Pixel-Grounded Prototypical Part Networks. CoRR abs/2309.14531 (2023) - [i14]Zachariah Carmichael, Walter J. Scheirer:
How Well Do Feature-Additive Explainers Explain Feature-Additive Predictors? CoRR abs/2310.18496 (2023) - [i13]Soumyendu Sarkar, Ashwin Ramesh Babu, Sajad Mousavi, Zachariah Carmichael, Vineet Gundecha, Sahand Ghorbanpour, Ricardo Luna Gutierrez, Antonio Guillen, Avisek Naug:
Benchmark Generation Framework with Customizable Distortions for Image Classifier Robustness. CoRR abs/2310.18626 (2023) - 2022
- [c6]Jonathan Takeshita, Zachariah Carmichael, Ryan Karl, Taeho Jung:
TERSE: Tiny Encryptions and Really Speedy Execution for Post-Quantum Private Stream Aggregation. SecureComm 2022: 331-352 - [i12]William Theisen, Daniel Gonzalez Cedre, Zachariah Carmichael, Daniel Moreira, Tim Weninger, Walter J. Scheirer:
Motif Mining: Finding and Summarizing Remixed Image Content. CoRR abs/2203.08327 (2022) - [i11]Zachariah Carmichael, Walter J. Scheirer:
Unfooling Perturbation-Based Post Hoc Explainers. CoRR abs/2205.14772 (2022) - [i10]Jonathan Takeshita, Zachariah Carmichael, Ryan Karl, Taeho Jung:
TERSE: Tiny Encryptions and Really Speedy Execution for Post-Quantum Private Stream Aggregation. IACR Cryptol. ePrint Arch. 2022: 829 (2022) - 2021
- [c5]Hamed Fatemi Langroudi, Vedant Karia, Zachariah Carmichael, Abdullah M. Zyarah, Tej Pandit, John L. Gustafson, Dhireesha Kudithipudi:
ALPS: Adaptive Quantization of Deep Neural Networks With GeneraLized PositS. CVPR Workshops 2021: 3100-3109 - [c4]Sophia J. Abraham, Zachariah Carmichael, Sreya Banerjee, Rosaura G. VidalMata, Ankit Agrawal, Md Nafee Al Islam, Walter J. Scheirer, Jane Cleland-Huang:
Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics Systems. WAIN@ICSE 2021: 113-120 - [i9]Sophia J. Abraham, Zachariah Carmichael, Sreya Banerjee, Rosaura G. VidalMata, Ankit Agrawal, Md Nafee Al Islam, Walter J. Scheirer, Jane Cleland-Huang:
Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics Systems. CoRR abs/2103.15053 (2021) - [i8]Zachariah Carmichael, Walter J. Scheirer:
On the Objective Evaluation of Post Hoc Explainers. CoRR abs/2106.08376 (2021) - [i7]Zachariah Carmichael, Tim Moon, Sam Ade Jacobs:
Learning Interpretable Models Through Multi-Objective Neural Architecture Search. CoRR abs/2112.08645 (2021)
2010 – 2019
- 2019
- [c3]Zachariah Carmichael, Hamed Fatemi Langroudi, Char Khazanov, Jeffrey Lillie, John L. Gustafson, Dhireesha Kudithipudi:
Deep Positron: A Deep Neural Network Using the Posit Number System. DATE 2019: 1421-1426 - [c2]Zachariah Carmichael, Benjamin Glasstone, Frank Cwitkowitz, Kenneth Alexopoulos, Robert Relyea, Raymond W. Ptucha:
Autonomous navigation using localization priors, sensor fusion, and terrain classification. Autonomous Vehicles and Machines 2019: 1-7 - [c1]Zachariah Carmichael, Dhireesha Kudithipudi:
Stochastic Tucker-Decomposed Recurrent Neural Networks for Forecasting. GlobalSIP 2019: 1-5 - [i6]Zachariah Carmichael, Hamed Fatemi Langroudi, Char Khazanov, Jeffrey Lillie, John L. Gustafson, Dhireesha Kudithipudi:
Performance-Efficiency Trade-off of Low-Precision Numerical Formats in Deep Neural Networks. CoRR abs/1903.10584 (2019) - [i5]Hamed Fatemi Langroudi, Zachariah Carmichael, Dhireesha Kudithipudi:
Deep Learning Training on the Edge with Low-Precision Posits. CoRR abs/1907.13216 (2019) - [i4]Hamed Fatemi Langroudi, Zachariah Carmichael, David Pastuch, Dhireesha Kudithipudi:
Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge. CoRR abs/1908.02386 (2019) - [i3]Zachariah Carmichael, Humza Syed, Dhireesha Kudithipudi:
Analysis of Wide and Deep Echo State Networks for Multiscale Spatiotemporal Time Series Forecasting. CoRR abs/1908.08380 (2019) - 2018
- [i2]Zachariah Carmichael, Humza Syed, Stuart Burtner, Dhireesha Kudithipudi:
Mod-DeepESN: Modular Deep Echo State Network. CoRR abs/1808.00523 (2018) - [i1]Zachariah Carmichael, Seyed Hamed Fatemi Langroudi, Char Khazanov, Jeffrey Lillie, John L. Gustafson, Dhireesha Kudithipudi:
Deep Positron: A Deep Neural Network Using the Posit Number System. CoRR abs/1812.01762 (2018)
Coauthor Index
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