2 citations · 2 across the 3 of their papers we have counts for
4 papers
Unrolling Lanczos for Ideal Low-pass Graph Filter Approximation
Parham Eftekhar, Gene Cheung, Mingxiao Liu +3
Low-pass (LP) filtering is a fundamental operation in graph signal processing (GSP). Among finite-order nodal-domain methods, Lanczos-based filtering provides more accurate approxi…
HypergraphFormer: Learning Hypergraphs from LLMs for Editable Floor Plan Generation
Nikita Klimenko, Hesam Salehipour, Parham Eftekhar +2
In this work, we propose HypergraphFormer, a novel and efficient approach to floor plan generation based on learning hypergraph representations with a large language model (LLM). T…
Lightweight Transformer for EEG Classification via Balanced Signed Graph Algorithm Unrolling
Junyi Yao, Parham Eftekhar, Gene Cheung +3
Samples of brain signals collected by EEG sensors have inherent anti-correlations that are well modeled by negative edges in a finite graph. To differentiate epilepsy patients from…
Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors
Tam Thuc Do, Parham Eftekhar, Seyed Alireza Hosseini +2
We build interpretable and lightweight transformer-like neural networks by unrolling iterative optimization algorithms that minimize graph smoothness priors -- the quadratic graph…