Search Results for author:
Found 7 papers, 2 papers with code
Machine Learning-Enhanced Aircraft Landing Scheduling under Uncertainties
This paper addresses aircraft delays, emphasizing their impact on safety and financial losses.
Air Traffic Controller Workload Level Prediction using Conformalized Dynamical Graph Learning
Air traffic control (ATC) is a safety-critical service system that demands constant attention from ground air traffic controllers (ATCos) to maintain daily aviation operations.
B-BACN: Bayesian Boundary-Aware Convolutional Network for Crack Characterization
Accurately detecting crack boundaries is crucial for reliability assessment and risk management of structures and materials, such as structural health monitoring, diagnostics, prognostics, and maintenance scheduling.
Posterior Regularized Bayesian Neural Network Incorporating Soft and Hard Knowledge Constraints
Neural Networks (NNs) have been widely {used in supervised learning} due to their ability to model complex nonlinear patterns, often presented in high-dimensional data such as images and text.
ProspectNet: Weighted Conditional Attention for Future Interaction Modeling in Behavior Prediction
In this work, we formulate the end-to-end joint prediction problem as a sequential learning process of marginal learning and joint learning of vehicle behaviors.
Decentralized Graph-Based Multi-Agent Reinforcement Learning Using Reward Machines
Experimental results show that local information is sufficient for DGRM and agents can accomplish complex tasks with the help of RM.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Evaluating the Robustness of Bayesian Neural Networks Against Different Types of Attacks
To evaluate the robustness gain of Bayesian neural networks on image classification tasks, we perform input perturbations, and adversarial attacks to the state-of-the-art Bayesian neural networks, with a benchmark CNN model as reference.
