37 citations · 40 across the 12 of their papers we have counts for
14 papers
Institutional Equity Holdings Prediction Using Node Affinities of Dynamic Graphs
Emad Izadifar, Zahed Rahmati
Institutional equity holdings disclosed in SEC Form 13F filings provide a rich temporal record of portfolio decisions by large investment managers. However, forecasting future allo…
Enhancing Graph Neural Networks Using Proximity Graphs for Dust Source Emission Forecasting
Maryam Sanisales, Zahed Rahmati, Ali Darvishi Boloorani +1
Accurate prediction of dust source emissions is critical for mitigating the significant environmental and health hazards posed by dust storms. Traditional forecasting methods often…
Semantic Reasoning in Medicine: The Role of Knowledge Graphs Across Five Key Domains
Haniye Sherafatmandjoo, Mohammad Akbari, Zahed Rahmati
Knowledge graphs (KGs) have emerged as a promising solution for integrating and reasoning over complex biomedical and clinical data in healthcare. By representing structured relati…
Where Black-box Drug-Target Interaction Prediction Models Look: Cross-Method Explainability
Ali Vefghi, Zahed Rahmati, Mohammad Akbari
Drug-target interaction (DTI) and affinity (DTA) predictors increasingly achieve strong benchmark scores, yet their internal use of sequence, fingerprint, and graph features often…
Drug-Target Interaction/Affinity Prediction: Deep Learning Models and Advances Review
Ali Vefghi, Zahed Rahmati, Mohammad Akbari
Drug discovery remains a slow and expensive process that involves many steps, from detecting the target structure to obtaining approval from the Food and Drug Administration (FDA),…
Relational Graph Convolutional Networks for Sentiment Analysis
Asal Khosravi, Zahed Rahmati, Ali Vefghi
With the growth of textual data across online platforms, sentiment analysis has become crucial for extracting insights from user-generated content. While traditional approaches and…
Edge2Node: Reducing Edge Prediction to Node Classification
Zahed Rahmati
Despite the success of graph neural network models in node classification, edge prediction (the task of predicting missing or potential links between nodes in a graph) remains a ch…
BERT-DRE: BERT with Deep Recursive Encoder for Natural Language Sentence Matching
Ehsan Tavan, Ali Rahmati, Maryam Najafi +2
This paper presents a deep neural architecture, for Natural Language Sentence Matching (NLSM) by adding a deep recursive encoder to BERT so called BERT with Deep Recursive Encoder…
RAC Drawings in Subcubic Area
Zahed Rahmati, Fatemeh Emami
In this paper, we study tradeoffs between curve complexity and area of Right Angle Crossing drawings (RAC drawings), which is a challenging theoretical problem in graph drawing. Gi…
Emanation Graph: A Plane Geometric Spanner with Steiner Points
Bardia Hamedmohseni, Zahed Rahmati, Debajyoti Mondal
An emanation graph of grade on a set of points is a plane spanner made by shooting equally spaced rays from each point, where the shorter rays stop the longer ones up…
Kinetic -Semi-Yao Graph and its Applications
Zahed Rahmati, Mohammad Ali Abam, Valerie King +1
This paper introduces a new proximity graph, called the -Semi-Yao graph (-SYG), on a set of points in , which is a supergraph of the -nearest neighbor gr…
Kinetic Reverse -Nearest Neighbor Problem
Zahed Rahmati, Valerie King, Sue Whitesides
This paper provides the first solution to the kinetic reverse -nearest neighbor (\rknn) problem in , which is defined as follows: Given a set of moving poi…
A Simple, Faster Method for Kinetic Proximity Problems
Zahed Rahmati, Mohammad Ali Abam, Valerie King +2
For a set of points in the plane, this paper presents simple kinetic data structures (KDS's) for solutions to some fundamental proximity problems, namely, the all nearest neigh…
Kinetic Data Structures for the Semi-Yao Graph and All Nearest Neighbors in R^d
Zahed Rahmati, Mohammad Ali Abam, Valerie King +1
This paper presents a simple kinetic data structure for maintaining all the nearest neighbors of a set of moving points in , where the trajectory of each point is…