Energy efficient path planning of autonomous underwater vehicles for environment modeling. - Diyuan Lu; Rongxin Cui; Ping Wang (MFI, 2014)

A Deep Residual Neural Network Based Framework for Epileptogenesis Detection in a Rodent Model with Single-Channel EEG Recordings. - Diyuan Lu; Sebastian Bauer; Valentin Neubert; Lara Sophie Costard; Felix Rosenow; Jochen Triesch (CISP-BMEI, 2019)

Residual Deep Convolutional Neural Network for EEG Signal Classification in Epilepsy. - Diyuan Lu; Jochen Triesch (CoRR, 2019)

Staging Epileptogenesis with Deep Neural Networks. - Diyuan Lu; Sebastian Bauer; Valentin Neubert; Lara Sophie Costard; Felix Rosenow; Jochen Triesch (BCB, 2020)

Towards Early Diagnosis of Epilepsy from EEG Data. - Diyuan Lu; Sebastian Bauer; Valentin Neubert; Lara Sophie Costard; Felix Rosenow; Jochen Triesch (MLHC, 2020)

Human-Expert-Level Brain Tumor Detection Using Deep Learning with Data Distillation And Augmentation. - Diyuan Lu; Nenad Polomac; Iskra Gacheva; Elke Hattingen; Jochen Triesch (ICASSP, 2021)

Multiple Instance Learning for Brain Tumor Detection from Magnetic Resonance Spectroscopy Data. - Diyuan Lu; Gerhard Kurz; Nenad Polomac; Iskra Gacheva; Elke Hattingen; Jochen Triesch (CoRR, 2021)

Diagnosing Epileptogenesis with Deep Anomaly Detection. - Amr Farahat; Diyuan Lu; Sebastian Bauer; Valentin Neubert; Lara Sophie Costard; Felix Rosenow; Jochen Triesch (MLHC, 2022)

Machine learning for healthcare with a focus on the early diagnosis of epilepsy and brain tumor detection - Diyuan Lu (2022)

Advancing Brain Tumor Detection with Multiple Instance Learning on Magnetic Resonance Spectroscopy Data. - Diyuan Lu; Gerhard Kurz; Nenad Polomac; Iskra Gacheva; Elke Hattingen; Jochen Triesch (ICANN (4), 2023)