Alexandra-Ioana Albu

According to our database1, Alexandra-Ioana Albu authored at least 12 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
X-CViT: An Explainable Vision Transformer Architecture for Classification of Cloud Images.
Proceedings of the 15th International Conference on Pattern Recognition Applications and Methods, 2026

2025
Diff-SySC: An Approach Using Diffusion Models for Semi-Supervised Image Classification.
Proceedings of the 17th International Conference on Agents and Artificial Intelligence, 2025

2023
<i>MM-StackEns</i>: A new deep multimodal stacked generalization approach for protein-protein interaction prediction.
Comput. Biol. Medicine, February, 2023

Improving radar echo extrapolation models using autoencoder-based perceptual losses.
Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 27th International Conference KES-2023, 2023

Temporal Ensembling-based Deep k-Nearest Neighbours for Learning with Noisy Labels.
Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

2022
NeXtNow: A Convolutional Deep Learning Model for the Prediction of Weather Radar Data for Nowcasting Purposes.
Remote. Sens., 2022

An Approach for Predicting Protein-Protein Interactions using Supervised Autoencoders.
Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 26th International Conference KES-2022, 2022

2021
AutoPPI: An Ensemble of Deep Autoencoders for Protein-Protein Interaction Prediction.
Entropy, 2021

Towards learning transferable embeddings for protein conformations using Variational Autoencoders.
Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES-2021, 2021

2020
Improved Slice-wise Tumour Detection in Brain MRIs by Computing Dissimilarities between Latent Representations.
CoRR, 2020

Analysing protein dynamics using machine learning based generative models.
Proceedings of the 14th IEEE International Symposium on Applied Computational Intelligence and Informatics, 2020

Tumor Detection in Brain MRIs by Computing Dissimilarities in the Latent Space of a Variational AutoEncoder.
Proceedings of the 2020 Northern Lights Deep Learning Workshop, 2020


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