Michail Chatzianastasis

Orcid: 0000-0002-9905-1646

According to our database1, Michail Chatzianastasis authored at least 16 papers between 2021 and 2024.

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

Timeline

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Bibliography

2024
Graph Linearization Methods for Reasoning on Graphs with Large Language Models.
CoRR, 2024

Signed Graph Autoencoder for Explainable and Polarization-Aware Network Embeddings.
CoRR, 2024

Metrics to Detect Small-Scale and Large-Scale Citation Orchestration.
CoRR, 2024

KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning.
CoRR, 2024

Geometric Self-Supervised Pretraining on 3D Protein Structures using Subgraphs.
CoRR, 2024

Neural Graph Generator: Feature-Conditioned Graph Generation using Latent Diffusion Models.
CoRR, 2024

Prot2Text: Multimodal Protein's Function Generation with GNNs and Transformers.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Explainable Multilayer Graph Neural Network for cancer gene prediction.
Bioinform., November, 2023

What Do GNNs Actually Learn? Towards Understanding their Representations.
CoRR, 2023

Neural Architecture Search with Multimodal Fusion Methods for Diagnosing Dementia.
Proceedings of the IEEE International Conference on Acoustics, 2023

Supervised Attention Using Homophily in Graph Neural Networks.
Proceedings of the Artificial Neural Networks and Machine Learning, 2023

Weisfeiler and Leman go Hyperbolic: Learning Distance Preserving Node Representations.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Graph Ordering Attention Networks.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Mass Enhanced Node Embeddings for Drug Repurposing.
Proceedings of the SETN 2022: 12th Hellenic Conference on Artificial Intelligence, Corfu, Greece, September 7, 2022

2021
Operation Embeddings for Neural Architecture Search.
CoRR, 2021

Graph-based Neural Architecture Search with Operation Embeddings.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021


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