14 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…
Transferring Neural Potentials For High Order Dependency Parsing
Farshad Noravesh
High order dependency parsing leverages high order features such as siblings or grandchildren to improve state of the art accuracy of current first order dependency parsers. The pr…
Semantic Tagging with LSTM-CRF
Farshad Noravesh
In the present paper, two models are presented namely LSTM-CRF and BERT-LSTM-CRF for semantic tagging of universal semantic tag dataset. The experiments show that the first model i…
Semantic Operator Prediction and Applications
Farshad Noravesh
In the present paper, semantic parsing challenges are briefly introduced and QDMR formalism in semantic parsing is implemented using sequence to sequence model with attention but u…
A Bayesian Approach To Graph Partitioning
Farshad Noravesh
A new algorithm based on bayesian inference for learning local graph conductance based on Gaussian Process(GP) is given that uses advanced MCMC convergence ideas to create a scalab…
Finding Many Sparse Cuts Using Entropy Maximization
Farshad Noravesh
A randomized algorithm for finding sparse cuts is given which is based on constructing a dual markov chain called multiscale rings process(MRP) and a new concept of entropy. It is…
Identifying OCRs in cfDNA WGS Data by Correlation Clustering
Farshad Noravesh, Fahimeh Palizban
In the recent decade, the emergence of liquid biopsy has significantly improved cancer monitoring and detection. Dying cells, including those originating from tumors, shed their DN…
Sparse Non-Convex Optimization For Higher Moment Portfolio Management
Farshad Noravesh
One of the reasons that higher order moment portfolio optimization methods are not fully used by practitioners in investment decisions is the complexity that these higher moments c…
Some connections between higher moments portfolio optimization methods
Farshad Noravesh, Kristiaan Kerstens
In this paper, different approaches to portfolio optimization having higher moments such as skewness and kurtosis are classified so that the reader can observe different paradigms…
Exact Post-selection Inference For Tracking S&P500
Farshad Noravesh, Hamid Boustanifar
The problem that is solved in this paper is known as index tracking. The method of Lasso is used to reduce the dimensions of S&P500 index which has many applications in both invest…