Mod-DeepESN: Modular Deep Echo State Network. - Zachariah Carmichael; Humza Syed; Stuart Burtner; Dhireesha Kudithipudi (CoRR, 2018)

Deep Positron: A Deep Neural Network Using the Posit Number System. - Zachariah Carmichael; Hamed Fatemi Langroudi; Char Khazanov; Jeffrey Lillie; John L. Gustafson; Dhireesha Kudithipudi (DATE, 2019)

Autonomous navigation using localization priors, sensor fusion, and terrain classification. - Zachariah Carmichael; Benjamin Glasstone; Frank Cwitkowitz; Kenneth Alexopoulos; Robert Relyea; Raymond W. Ptucha (Autonomous Vehicles and Machines, 2019)

Stochastic Tucker-Decomposed Recurrent Neural Networks for Forecasting. - Zachariah Carmichael; Dhireesha Kudithipudi (GlobalSIP, 2019)

Performance-Efficiency Trade-off of Low-Precision Numerical Formats in Deep Neural Networks. - Zachariah Carmichael; Hamed Fatemi Langroudi; Char Khazanov; Jeffrey Lillie; John L. Gustafson; Dhireesha Kudithipudi (CoRR, 2019)

Deep Learning Training on the Edge with Low-Precision Posits. - Hamed Fatemi Langroudi; Zachariah Carmichael; Dhireesha Kudithipudi (CoRR, 2019)

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge. - Hamed Fatemi Langroudi; Zachariah Carmichael; David Pastuch; Dhireesha Kudithipudi (CoRR, 2019)

Analysis of Wide and Deep Echo State Networks for Multiscale Spatiotemporal Time Series Forecasting. - Zachariah Carmichael; Humza Syed; Dhireesha Kudithipudi (CoRR, 2019)

ALPS: Adaptive Quantization of Deep Neural Networks With GeneraLized PositS. - Hamed Fatemi Langroudi; Vedant Karia; Zachariah Carmichael; Abdullah M. Zyarah; Tej Pandit; John L. Gustafson; Dhireesha Kudithipudi (CVPR Workshops, 2021)

Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics Systems. - Sophia J. Abraham; Zachariah Carmichael; Sreya Banerjee; Rosaura G. VidalMata; Ankit Agrawal 002; Md Nafee Al Islam; Walter J. Scheirer; Jane Cleland-Huang (WAIN@ICSE, 2021)

On the Objective Evaluation of Post Hoc Explainers. - Zachariah Carmichael; Walter J. Scheirer (CoRR, 2021)

Learning Interpretable Models Through Multi-Objective Neural Architecture Search. - Zachariah Carmichael; Tim Moon; Sam Ade Jacobs (CoRR, 2021)

TERSE: Tiny Encryptions and Really Speedy Execution for Post-Quantum Private Stream Aggregation. - Jonathan Takeshita; Zachariah Carmichael; Ryan Karl; Taeho Jung (IACR Cryptol. ePrint Arch., 2022)

Unfooling Perturbation-Based Post Hoc Explainers. - Zachariah Carmichael; Walter J. Scheirer (AAAI, 2023)

Motif Mining: Finding and Summarizing Remixed Image Content. - William Theisen; Daniel Gonzalez Cedre; Zachariah Carmichael; Daniel Moreira; Tim Weninger; Walter J. Scheirer (WACV, 2023)

HomOpt: A Homotopy-Based Hyperparameter Optimization Method. - Sophia J. Abraham; Kehelwala D. G. Maduranga; Jeffery Kinnison; Zachariah Carmichael; Jonathan D. Hauenstein; Walter J. Scheirer (CoRR, 2023)

How Well Do Feature-Additive Explainers Explain Feature-Additive Predictors? - Zachariah Carmichael; Walter J. Scheirer (CoRR, 2023)

This Probably Looks Exactly Like That: An Invertible Prototypical Network. - Zachariah Carmichael; Timothy Redgrave; Daniel Gonzalez Cedre; Walter J. Scheirer (ECCV (37), 2024)

Pixel-Grounded Prototypical Part Networks. - Zachariah Carmichael; Suhas Lohit; Anoop Cherian; Michael J. Jones 001; Walter J. Scheirer (WACV, 2024)

Benchmark Generation Framework with Customizable Distortions for Image Classifier Robustness. - Soumyendu Sarkar; Ashwin Ramesh Babu; Sajad Mousavi; Zachariah Carmichael; Vineet Gundecha; Sahand Ghorbanpour; Ricardo Luna Gutierrez 001; Antonio Guillen; Avisek Naug (WACV, 2024)