13 citations · 46 across the 15 of their papers we have counts for
7 papers · 1 filter
PRICE: A Systematic Study of LLM Adaptation Choices for Bitcoin Price Forecasting
Maryam Fakhari, Mehran Safayani
Cryptocurrency markets exhibit extreme volatility and non-stationary dynamics that challenge conventional forecasting methods. Although Large Language Models (LLMs) have shown prom…
ASDFormer: A Transformer with Mixtures of Pooling-Classifier Experts for Robust Autism Diagnosis and Biomarker Discovery
Mohammad Izadi, Mehran Safayani
Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition marked by disruptions in brain connectivity. Functional MRI (fMRI) offers a non-invasive window into large-…
A Dual-Attention Graph Network for fMRI Data Classification
Amirali Arbab, Zeinab Davarani, Mehran Safayani
Understanding the complex neural activity dynamics is crucial for the development of the field of neuroscience. Although current functional MRI classification approaches tend to be…
Knowledge Distillation on Spatial-Temporal Graph Convolutional Network for Traffic Prediction
Mohammad Izadi, Mehran Safayani, Abdolreza Mirzaei
Efficient real-time traffic prediction is crucial for reducing transportation time. To predict traffic conditions, we employ a spatio-temporal graph neural network (ST-GNN) to mode…
HDGL: A hierarchical dynamic graph representation learning model for brain disorder classification
Parnian Jalali, Mehran Safayani
The human brain can be considered as complex networks, composed of various regions that continuously exchange their information with each other, forming the brain network graph, fr…
Clustering based on Mixtures of Sparse Gaussian Processes
Zahra Moslehi, Abdolreza Mirzaei, Mehran Safayani
Creating low dimensional representations of a high dimensional data set is an important component in many machine learning applications. How to cluster data using their low dimensi…
Deep Graph Clustering via Mutual Information Maximization and Mixture Model
Maedeh Ahmadi, Mehran Safayani, Abdolreza Mirzaei
Attributed graph clustering or community detection which learns to cluster the nodes of a graph is a challenging task in graph analysis. In this paper, we introduce a contrastive l…