Xiaoyu Mo
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View article: Sequence Accumulation and Beyond: Infinite Context Length on Single GPU and Large Clusters
Sequence Accumulation and Beyond: Infinite Context Length on Single GPU and Large Clusters Open
Linear sequence modeling methods, such as linear attention, state space modeling, and linear RNNs, have recently been recognized as potential alternatives to softmax attention thanks to their linear complexity and competitive performance. …
View article: Hybrid-Prediction Integrated Planning for Autonomous Driving
Hybrid-Prediction Integrated Planning for Autonomous Driving Open
Autonomous driving systems require the ability to fully understand and predict the surrounding environment to make informed decisions in complex scenarios. Recent advancements in learning-based systems have highlighted the importance of in…
View article: Driver Steering Behaviour Modelling Based on Neuromuscular Dynamics and Multi-Task Time-Series Transformer
Driver Steering Behaviour Modelling Based on Neuromuscular Dynamics and Multi-Task Time-Series Transformer Open
Driver steering intention prediction provides an augmented solution to the design of an onboard collaboration mechanism between human driver and intelligent vehicle. In this study, a multi-task sequential learning framework is developed to…
View article: CCDC 2284506: Experimental Crystal Structure Determination
CCDC 2284506: Experimental Crystal Structure Determination Open
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available …
View article: Designing Loving-Kindness Meditation in Virtual Reality for Long-Distance Romantic Relationships
Designing Loving-Kindness Meditation in Virtual Reality for Long-Distance Romantic Relationships Open
Loving-kindness meditation (LKM) is used in clinical psychology for couples' relationship therapy, but physical isolation can make the relationship more strained and inaccessible to LKM. Virtual reality (VR) can provide immersive LKM activ…
View article: CCDC 2056319: Experimental Crystal Structure Determination
CCDC 2056319: Experimental Crystal Structure Determination Open
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available …
View article: Map-Adaptive Multimodal Trajectory Prediction Using Hierarchical Graph Neural Networks
Map-Adaptive Multimodal Trajectory Prediction Using Hierarchical Graph Neural Networks Open
Predicting the multimodal future motions of neighboring agents is essential for an autonomous vehicle to navigate complex scenarios. It is challenging as the motion of an agent is affected by the complex interaction among itself, other age…
View article: CCDC 2236954: Experimental Crystal Structure Determination
CCDC 2236954: Experimental Crystal Structure Determination Open
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available …
View article: A Generalized Multi-Modal Fusion Detection Framework
A Generalized Multi-Modal Fusion Detection Framework Open
LiDAR point clouds have become the most common data source in autonomous driving. However, due to the sparsity of point clouds, accurate and reliable detection cannot be achieved in specific scenarios. Because of their complementarity with…
View article: Rh-Catalyzed C—H Functionalization Reaction between 3-Diazoindolin-2-imines and Pyrazolones for the Construction of 3-Pyrazolyl Indoles
Rh-Catalyzed C—H Functionalization Reaction between 3-Diazoindolin-2-imines and Pyrazolones for the Construction of 3-Pyrazolyl Indoles Open
A highly efficient C-H functionalization reaction of α-imino carbenes and pyrazolones in the presence of Rh2(OAc)4 has been reported.This methodology provides a rapid and straightforward approach toward a variety of structurally diverse 3-…
View article: Reducing Stress and Anxiety in the Metaverse: A Systematic Review of Meditation, Mindfulness and Virtual Reality
Reducing Stress and Anxiety in the Metaverse: A Systematic Review of Meditation, Mindfulness and Virtual Reality Open
Meditation, or mindfulness, is widely used to improve mental health. With the emergence of Virtual Reality technology, many studies have provided evidence that meditation with VR can bring health benefits. However, to our knowledge, there …
View article: Augmenting Reinforcement Learning with Transformer-based Scene Representation Learning for Decision-making of Autonomous Driving
Augmenting Reinforcement Learning with Transformer-based Scene Representation Learning for Decision-making of Autonomous Driving Open
Decision-making for urban autonomous driving is challenging due to the stochastic nature of interactive traffic participants and the complexity of road structures. Although reinforcement learning (RL)-based decision-making scheme is promis…
View article: ReCoAt: A Deep Learning-based Framework for Multi-Modal Motion Prediction in Autonomous Driving Application
ReCoAt: A Deep Learning-based Framework for Multi-Modal Motion Prediction in Autonomous Driving Application Open
This paper proposes a novel deep learning framework for multi-modal motion prediction. The framework consists of three parts: recurrent neural networks to process the target agent's motion process, convolutional neural networks to process …
View article: Multi-task Driver Steering Behaviour Modeling Using Time-Series Transformer
Multi-task Driver Steering Behaviour Modeling Using Time-Series Transformer Open
Human intention prediction provides an augmented solution for the design of assistants and collaboration between the human driver and intelligent vehicles. In this study, a multi-task sequential learning framework is developed to predict f…
View article: Multi-Agent Trajectory Prediction With Heterogeneous Edge-Enhanced Graph Attention Network
Multi-Agent Trajectory Prediction With Heterogeneous Edge-Enhanced Graph Attention Network Open
Simultaneous trajectory prediction for multiple heterogeneous traffic participants is essential for safe and efficient operation of connected automated vehicles under complex driving situations. Two main challenges for this task are to han…
View article: Deep learning-based interaction-aware trajectory prediction for autonomous vehicles
Deep learning-based interaction-aware trajectory prediction for autonomous vehicles Open
Predicting future trajectories of surrounding agents and conducting motion planning based on interaction predictions are of great importance for ensuring the safety and efficiency of autonomous driving in real-world scenarios, especially u…
View article: Multi-modal Motion Prediction with Transformer-based Neural Network for Autonomous Driving
Multi-modal Motion Prediction with Transformer-based Neural Network for Autonomous Driving Open
Predicting the behaviors of other agents on the road is critical for autonomous driving to ensure safety and efficiency. However, the challenging part is how to represent the social interactions between agents and output different possible…
View article: Graph and Recurrent Neural Network-based Vehicle Trajectory Prediction For Highway Driving
Graph and Recurrent Neural Network-based Vehicle Trajectory Prediction For Highway Driving Open
Integrating trajectory prediction to the decision-making and planning modules of modular autonomous driving systems is expected to improve the safety and efficiency of self-driving vehicles. However, a vehicle's future trajectory predictio…
View article: Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Trajectory Prediction
Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Trajectory Prediction Open
Simultaneous trajectory prediction for multiple heterogeneous traffic participants is essential for the safe and efficient operation of connected automated vehicles under complex driving situations in the real world. The multi-agent predic…
View article: Toward Safe and Smart Mobility: Energy-Aware Deep Learning for Driving Behavior Analysis and Prediction of Connected Vehicles
Toward Safe and Smart Mobility: Energy-Aware Deep Learning for Driving Behavior Analysis and Prediction of Connected Vehicles Open
Connected automated driving technologies have shown tremendous improvement in recent years. However, it is still not clear how driving behaviors and energy consumption correlate with each other and to what extent these factors related to c…
View article: ReCoG: A Deep Learning Framework with Heterogeneous Graph for Interaction-Aware Trajectory Prediction
ReCoG: A Deep Learning Framework with Heterogeneous Graph for Interaction-Aware Trajectory Prediction Open
Predicting the future trajectory of surrounding vehicles is essential for the navigation of autonomous vehicles in complex real-world driving scenarios. It is challenging as a vehicle's motion is affected by many factors, including its sur…
View article: Interaction-Aware Trajectory Prediction of Connected Vehicles using CNN-LSTM Networks
Interaction-Aware Trajectory Prediction of Connected Vehicles using CNN-LSTM Networks Open
Predicting the future trajectory of a surrounding vehicle in congested traffic is one of the basic abilities of an autonomous vehicle. In congestion, a vehicle's future movement is the result of its interaction with surrounding vehicles. A…
View article: Learning to Compose and Reason with Language Tree Structures for Visual Grounding
Learning to Compose and Reason with Language Tree Structures for Visual Grounding Open
Grounding natural language in images, such as localizing "the black dog on\nthe left of the tree", is one of the core problems in artificial intelligence,\nas it needs to comprehend the fine-grained and compositional language space.\nHowev…
View article: Distributed Function Calculation over Noisy Networks
Distributed Function Calculation over Noisy Networks Open
Considering any connected network with unknown initial states for all nodes, the nearest-neighbor rule is utilized for each node to update its own state at every discrete-time step. Distributed function calculation problem is defined for o…