Morteza Haghir Chehreghani
Showing 35 publications
A Deep Learning Framework for Generation and Analysis of Driving Scenario Trajectories
Online Learning of Network Bottlenecks via Minimax Paths
Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction
Deep Q-learning: a robust control approach
A Combinatorial Semi-Bandit Approach to Charging Station Selection for Electric Vehicles
Online Learning of Energy Consumption for Navigation of Electric Vehicles
Autonomous Drug Design with Multi-Armed Bandits
TEP-GNN: Accurate Execution Time Prediction of Functional Tests Using Graph Neural Networks
On Using Node Indices and Their Correlations for Fake Account Detection
Efficient Optimization of Dominant Set Clustering with Frank-Wolfe Algorithms
Analysis of Knowledge Transfer in Kernel Regime
Passive and Active Learning of Driver Behavior from Electric Vehicles
A Contextual Combinatorial Semi-Bandit Approach to Network Bottleneck Identification
Graph Clustering Using Node Embeddings: An Empirical Study
An Online Learning Approach for Vehicle Usage Prediction During COVID-19
Shift of pairwise similarities for data clustering
Using Active Learning to Develop Machine Learning Models for Reaction Yield Prediction
A unified framework for online trip destination prediction
Memory-Efficient Minimax Distance Measures
Do Kernel and Neural Embeddings Help in Training and Generalization?
Trip Prediction by Leveraging Trip Histories from Neighboring Users
Active learning of driving scenario trajectories
Controlling gene expression with deep generative design of regulatory DNA
Reliable Agglomerative Clustering
Shallow Node Representation Learning using Centrality Indices
Vehicle Motion Trajectories Clustering via Embedding Transitive Relations
Model-Centric and Data-Centric Aspects of Active Learning for Deep Neural Networks
An online learning framework for energy-efficient navigation of electric vehicles
Learning representations from dendrograms
Unsupervised representation learning with Minimax distance measures
Accelerated proximal incremental algorithm schemes for non-strongly convex functions
Generation of Driving Scenario Trajectories with Generative Adversarial Networks
A Non-Convex Optimization Approach to Correlation Clustering
Efficient context-aware K-nearest neighbor search
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Showing 8 research projects
LEAR: Robust LEArning methods for electric vehicle Route selection
Energy-efficient autopilot (EcoPilot)
Energy-based models for supervised deep neural networks and their applications
Adaptive Neural Controller for Future Renewable Fuels
Real-Time Robust and AdaptIve Learning in ElecTric VEhicles (RITE)
Modelling and optimization of energy management systems for plug-in hybrid vehicles
AI-assisted real-time digital twin for electric drivetrains
EENE: Energy Effective Navigation for EVs