Peyman M. Kiasari

According to our database, Peyman M. Kiasari authored at least 9 papers between 2024 and 2026.

Collaborative distances:

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

2026

Modeling and Analysis of the 8 Filters from the "Master Key Filters Hypothesis" for Depthwise-Separable Deep Networks in Relation to Idealized Receptive Fields Based on Scale-Space Theory.

Tony Lindeberg, Zahra Babaiee, Peyman M. Kiasari

J. Math. Imaging Vis., June, 2026

2025

Modelling and analysis of the 8 filters from the "master key filters hypothesis" for depthwise-separable deep networks in relation to idealized receptive fields based on scale-space theory.

Tony Lindeberg, Zahra Babaiee, Peyman M. Kiasari

CoRR, September, 2025

The Quest for Universal Master Key Filters in DS-CNNs.

Zahra Babaiee, Peyman M. Kiasari, Daniela Rus, Radu Grosu

CoRR, September, 2025

Are Programming Paradigms Paradigms? A Critical Examination of Floyd's Appropriation of Kuhn's Philosophy.

Peyman M. Kiasari

CoRR, May, 2025

Visual Graph Arena: Evaluating Visual Conceptualization of Vision and Multimodal Large Language Models.

Zahra Babaiee, Peyman M. Kiasari, Daniela Rus, Radu Grosu

Proceedings of the Forty-second International Conference on Machine Learning, 2025

The Master Key Filters Hypothesis: Deep Filters Are General.

Zahra Babaiee, Peyman M. Kiasari, Daniela Rus, Radu Grosu

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

The Master Key Filters Hypothesis: Deep Filters Are General in DS-CNNs.

Zahra Babaiee, Peyman M. Kiasari, Daniela Rus, Radu Grosu

CoRR, 2024

Neural Echos: Depthwise Convolutional Filters Replicate Biological Receptive Fields.

Zahra Babaiee, Peyman M. Kiasari, Daniela Rus, Radu Grosu

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels.

Zahra Babaiee, Peyman M. Kiasari, Daniela Rus, Radu Grosu

Proceedings of the Twelfth International Conference on Learning Representations, 2024