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07/20/2023
Air Traffic Controller Workload Level Prediction using Conformalized Dynamical Graph Learning
Air traffic control (ATC) is a safety-critical service system that deman...
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05/27/2023
Reinforcement Learning With Reward Machines in Stochastic Games
We investigate multi-agent reinforcement learning for stochastic games w...
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05/12/2023
ArtGPT-4: Artistic Vision-Language Understanding with Adapter-enhanced MiniGPT-4
In recent years, large language models (LLMs) have made significant prog...
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03/05/2023
CAMEL: Curvature-Augmented Manifold Embedding and Learning
A novel method, named Curvature-Augmented Manifold Embedding and Learnin...
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02/27/2023
Hulk: Graph Neural Networks for Optimizing Regionally Distributed Computing Systems
Large deep learning models have shown great potential for delivering exc...
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02/14/2023
B-BACN: Bayesian Boundary-Aware Convolutional Network for Crack Characterization
The accurate detection of crack boundaries is crucial for various purpos...
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12/12/2022
RPN: A Word Vector Level Data Augmentation Algorithm in Deep Learning for Language Understanding
This paper presents a new data augmentation algorithm for natural unders...
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10/16/2022
Posterior Regularized Bayesian Neural Network Incorporating Soft and Hard Knowledge Constraints
Neural Networks (NNs) have been widely used in supervised learning due t...
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08/08/2022
Neural Optimization Machine: A Neural Network Approach for Optimization
A novel neural network (NN) approach is proposed for constrained optimiz...
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11/13/2021
Obstacle Avoidance for UAS in Continuous Action Space Using Deep Reinforcement Learning
Obstacle avoidance for small unmanned aircraft is vital for the safety o...
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10/15/2021
Robust physics discovery via supervised and unsupervised pattern recognition using the Euler characteristic
Machine learning approaches have been widely used for discovering the un...
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09/30/2021
Decentralized Graph-Based Multi-Agent Reinforcement Learning Using Reward Machines
In multi-agent reinforcement learning (MARL), it is challenging for a co...
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06/17/2021
Evaluating the Robustness of Bayesian Neural Networks Against Different Types of Attacks
To evaluate the robustness gain of Bayesian neural networks on image cla...
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01/31/2021
Robust Data-Driven Discovery of Partial Differential Equations under Uncertainties
Robust physics (e.g., governing equations and laws) discovery is of grea...
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01/31/2020
FEA-Net: A Physics-guided Data-driven Model for Efficient Mechanical Response Prediction
An innovative physics-guided learning algorithm for predicting the mecha...
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12/22/2016