Tumor Detection in Brain MRIs by Computing Dissimilarities in the Latent Space of a Variational AutoEncoder. - Alexandra-Ioana Albu; Alina Enescu; Luigi Malagò (NLDL, 2020)

Analysing protein dynamics using machine learning based generative models. - Alexandra-Ioana Albu; Gabriela Czibula (SACI, 2020)

Improved Slice-wise Tumour Detection in Brain MRIs by Computing Dissimilarities between Latent Representations. - Alexandra-Ioana Albu; Alina Enescu; Luigi Malagò (CoRR, 2020)

Towards learning transferable embeddings for protein conformations using Variational Autoencoders. - Alexandra-Ioana Albu (KES, 2021)

AutoPPI: An Ensemble of Deep Autoencoders for Protein-Protein Interaction Prediction. - Gabriela Czibula; Alexandra-Ioana Albu; Maria-Iuliana Bocicor; Camelia Chira (Entropy, 2021)

An Approach for Predicting Protein-Protein Interactions using Supervised Autoencoders. - Alexandra-Ioana Albu (KES, 2022)

NeXtNow: A Convolutional Deep Learning Model for the Prediction of Weather Radar Data for Nowcasting Purposes. - Alexandra-Ioana Albu; Gabriela Czibula; Andrei Mihai; István Gergely Czibula; Sorin Burcea; Abdelkader Mezghani (Remote. Sens., 2022)

Temporal Ensembling-based Deep k-Nearest Neighbours for Learning with Noisy Labels. - Alexandra-Ioana Albu (ESANN, 2023)

Improving radar echo extrapolation models using autoencoder-based perceptual losses. - Alexandra-Ioana Albu (KES, 2023)

MM-StackEns: A new deep multimodal stacked generalization approach for protein-protein interaction prediction. - Alexandra-Ioana Albu; Maria-Iuliana Bocicor; Gabriela Czibula (Comput. Biol. Medicine, 2023)

Diff-SySC: An Approach Using Diffusion Models for Semi-Supervised Image Classification. - Paul-Dumitru Orasan; Alexandra-Ioana Albu; Gabriela Czibula (ICAART (3), 2025)