The faster proximal algorithm, the better unfolded deep learning architecture ? The study case of image denoising. - Hoang Trieu Vy Le; Nelly Pustelnik; Marion Foare (EUSIPCO, 2022)

Proximal Based Strategies for Solving Discrete Mumford-Shah With Ambrosio-Tortorelli Penalization on Edges. - Hoang Trieu Vy Le; Marion Foare; Nelly Pustelnik (IEEE Signal Process. Lett., 2022)

PNN: From proximal algorithms to robust unfolded image denoising networks and Plug-and-Play methods. - Hoang Trieu Vy Le; Audrey Repetti; Nelly Pustelnik (CoRR, 2023)

Variations on the Mumford-Shah functional for interface detection in degraded images : from proximal algorithms to unrolled architectures. (Variations sur la fonctionnelle de Mumford-Shah pour la détection d'interfaces dans des images dégradées : des algorithmes proximaux aux architectures déroulées). - Hoang Trieu Vy Le (2023)

Unfolded Proximal Neural Networks for Robust Image Gaussian Denoising. - Hoang Trieu Vy Le; Audrey Repetti; Nelly Pustelnik (IEEE Trans. Image Process., 2024)

Embedding Blake-Zisserman Regularization in Unfolded Proximal Neural Networks for Enhanced Edge Detection. - Hoang Trieu Vy Le; Marion Foare; Audrey Repetti; Nelly Pustelnik (IEEE Signal Process. Lett., 2025)