Andrew Arash Mahyari

According to our database, Andrew Arash Mahyari authored at least 12 papers between 2024 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Transductive One-Shot Learning Meet Subspace Decomposition.

Kyle Stein, Andrew Arash Mahyari, Guillermo Francia III, Eman El-Sheikh

CoRR, April, 2025

Proactive Disentangled Modeling of Trigger-Object Pairings for Backdoor Defense.

Kyle Stein, Andrew Arash Mahyari, Guillermo Francia III, Eman El-Sheikh

Comput. Mater. Continua, 2025

Packet Inspection Transformer: A Self-Supervised Journey to Unseen Malware Detection With Few Samples.

Kyle Stein, Guillermo Francia III, Eman El-Sheikh, Andrew Arash Mahyari

IEEE Access, 2025

Proactive Adversarial Defense: Harnessing Prompt Tuning in Vision-Language Models to Detect Unseen Backdoored Images.

Kyle Stein, Andrew Arash Mahyari, Guillermo Francia, Eman El-Sheikh

Proceedings of the IEEE Military Communications Conference, 2025

Visual Adaptive Prompting for Compositional Zero-Shot Learning.

Kyle Stein, Andrew Arash Mahyari, Guillermo Francia, Eman El-Sheikh

Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025

Loop Closure Detection Revisited: A Clustering Perspective.

Don Yates, Hakki Erhan Sevil, Andrew Arash Mahyari

Proceedings of the Applied Imagery Pattern Recognition, 2025

Adaptive Additive Parameter Updates of Vision Transformers for Few-Shot Continual Learning.

Kyle Stein, Andrew Arash Mahyari, Guillermo Francia, Eman El-Sheikh

Proceedings of the 59th Asilomar Conference on Signals, 2025

Prompt-Conditioned Vision-Language Models for Detecting Unseen Backdoor Images.

Kyle Stein, Andrew Arash Mahyari, Guillermo Francia, Eman El-Sheikh

Proceedings of the 59th Asilomar Conference on Signals, 2025

2024

Toward a Real-Time Digital Twin Framework for Infection Mitigation During Air Travel.

Ashok Srinivasan, Satkkeerthi Sriram, Sirish Namilae, Andrew Arash Mahyari

CoRR, 2024

Towards Novel Malicious Packet Recognition: A Few-Shot Learning Approach.

Kyle Stein, Andrew Arash Mahyari, Guillermo A. Francia III, Eman El-Sheikh

Proceedings of the IEEE Military Communications Conference, 2024

Harnessing the Power of LLMs in Source Code Vulnerability Detection.

Andrew Arash Mahyari

Proceedings of the IEEE Military Communications Conference, 2024

Training Variational Autoencoders for Population Synthesis in Public Health with Missing Data.

Nathan Blackthorn, Andrew Arash Mahyari, Ashok Srinivasan

Proceedings of the IEEE International Conference on Big Data, 2024