From the 1 of 4 linked papers with an AI index.
4 papers
Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding
Tam Thuc Do, Philip A. Chou, Gene Cheung
The paper proposes a deep-unrolled, feed‑forward network to perform lossy attribute compression for 3D point clouds by projecting attributes onto multi‑resolution B‑spline bases an…
Lightweight and Interpretable Transformer via Mixed Graph Algorithm Unrolling for Traffic Forecast
Ji Qi, Tam Thuc Do, Mingxiao Liu +4
Unlike conventional "black-box" transformers with classical self-attention mechanism, we build a lightweight and interpretable transformer-like neural net by unrolling a mixed-grap…
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…