Variational Auto-Encoders Without Graph Coarsening For Fine Mesh Learning. - Nicolas Vercheval; Hendrik De Bie; Aleksandra Pizurica (ICIP, 2020)

Hierarchical Variational Autoencoders For Visual Counterfactuals. - Nicolas Vercheval; Aleksandra Pizurica (ICIP, 2021)

Hierarchical Variational Autoencoder for Visual Counterfactuals. - Nicolas Vercheval; Aleksandra Pizurica (CoRR, 2021)

Counterfactual Functional Connectomes for Neurological Classifier Selection. - Nicolas Vercheval; Marin Bencevic; Dario Muzevic; Irena Galic; Aleksandra Pizurica (EUSIPCO, 2023)

GPU Rasterization-Based 3D LiDAR Simulation for Deep Learning. - Leon Denis; Remco Royen; Quentin Bolsée; Nicolas Vercheval; Aleksandra Pizurica; Adrian Munteanu 001 (Sensors, 2023)

Not All Boxes Are Equal: Learning to Optimize Bounding Boxes With Discriminative Distributions in Optical Remote Sensing Images. - Qi Ming; Lingjuan Miao; Zhiqiang Zhou; Nicolas Vercheval; Aleksandra Pizurica (IEEE Trans. Geosci. Remote. Sens., 2024)

PCGen: A Fully Parallelizable Point Cloud Generative Model. - Nicolas Vercheval; Remco Royen; Adrian Munteanu 001; Aleksandra Pizurica (Sensors, 2024)