5 papers
VQ-SAD: Vector Quantized Structure Aware Diffusion For Molecule Generation
Farshad Noravesh, Reza Haffari, Layki Soon +1
Many diffusion based molecule generation methods ignore the symbolic information of molecules and represent the atom and bond type as one hot representation. Methods based on Morga…
Are Graph Attention Networks Able to Model Structural Information?
Farshad Noravesh, Reza Haffari, Layki Soon +1
Graph Attention Networks (GATs) have emerged as powerful models for learning expressive representations from such data by adaptively weighting neighboring nodes through attention m…
LGRPool: Hierarchical Graph Pooling Via Local-Global Regularisation
Farshad Noravesh, Reza Haffari, Layki Soon +1
Hierarchical graph pooling(HGP) are designed to consider the fact that conventional graph neural networks(GNN) are inherently flat and are also not multiscale. However, most HGP me…
Attending To Syntactic Information In Biomedical Event Extraction Via Graph Neural Networks
Farshad Noravesh, Reza Haffari, Ong Huey Fang +3
Many models are proposed in the literature on biomedical event extraction(BEE). Some of them use the shortest dependency path(SDP) information to represent the argument classificat…
BioNCERE: Non-Contrastive Enhancement For Relation Extraction In Biomedical Texts
Farshad Noravesh
State-of-the-art models for relation extraction (RE) in the biomedical domain consider finetuning BioBERT using classification, but they may suffer from the anisotropy problem. Con…