Spatial-Temporal Large Language Model for Traffic Prediction
The paper presents a Spatial-Temporal Large Language Model (ST-LLM) for traffic prediction. The ST-LLM redefines the timesteps…
Multi-Agent Reinforcement Learning for Maritime Operational Technology Cyber Security
This academic paper discusses the potential of autonomous cyber defense in industrial control systems, with a focus…
A novel hybrid time-varying graph neural network for traffic flow forecasting
The authors propose a Hybrid Time-Varying Graph Neural Network (HTVGNN) to improve traffic flow predictions. Traditional methods…
Comprehensive OOD Detection Improvements
The article by Anish Lakkapragada, Amol Khanna, Edward Raff, and Nathan Inkawhich discusses the importance of detecting…
Transfer Learning in Human Activity Recognition: A Survey
The article presents a survey on transfer learning methods applied in the field of Human Activity Recognition…
Divide and not forget: Ensemble of selectively trained experts in Continual Learning
The article presents a novel approach in class-incremental learning named SEED. It addresses the issue of models…
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products
The article talks about the development of equivariant neural networks for the E(3) group which is important…
Robustness Evaluation of Machine Learning Models for Robot Arm Action Recognition in Noisy Environments
The paper investigates the challenge of recognizing distinct arm movements of robots in noisy environments using machine…
WindSeer: Real-time volumetric wind prediction over complex terrain aboard a small UAV
The paper presents WindSeer, a neural network trained with synthetic data from computational fluid dynamics simulations. It…
Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics Learning and Control
The article discusses the use of machine learning techniques for robot dynamics learning and control. The authors…