43 citations · 108 across the 22 of their papers we have counts for
23 papers
Heterogeneous Information-Bottleneck Coordination Graphs for Multi-Agent Reinforcement Learning
Wei Duan, Junyu Xuan, En Yu +2
Coordination graphs are a central abstraction in cooperative multi-agent reinforcement learning (MARL), yet existing sparse-graph learners lack a theoretically grounded mechanism t…
VGAS: Value-Guided Action-Chunk Selection for Few-Shot Vision-Language-Action Adaptation
Changhua Xu, En Yu, Junyu Xuan +1
Vision--Language--Action (VLA) models bridge multimodal reasoning with physical control, but adapting them to new tasks with scarce demonstrations remains unreliable. While fine-tu…
Bandwidth-constrained Variational Message Encoding for Cooperative Multi-agent Reinforcement Learning
Wei Duan, Jie Lu, En Yu +1
Graph-based multi-agent reinforcement learning (MARL) enables coordinated behavior under partial observability by modeling agents as nodes and communication links as edges. While r…
Bayesian Ego-graph Inference for Networked Multi-Agent Reinforcement Learning
Wei Duan, Jie Lu, Junyu Xuan
In networked multi-agent reinforcement learning (Networked-MARL), decentralized agents must act under local observability and constrained communication over fixed physical graphs.…
Functional Stochastic Gradient MCMC for Bayesian Neural Networks
Mengjing Wu, Junyu Xuan, Jie Lu
Classical parameter-space Bayesian inference for Bayesian neural networks (BNNs) suffers from several unresolved prior issues, such as knowledge encoding intractability and patholo…
LSTM Autoencoder-based Deep Neural Networks for Barley Genotype-to-Phenotype Prediction
Guanjin Wang, Junyu Xuan, Penghao Wang +2
Artificial Intelligence (AI) has emerged as a key driver of precision agriculture, facilitating enhanced crop productivity, optimized resource use, farm sustainability, and informe…