Author

Jianlei Yang

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#edge computing Oct 2026

High-Performance Bayesian Neural Network Inference Accelerator Based on FPGA

Bayesian Neural Networks (BNNs) offer robust uncertainty estimation capabilities through probabilistic modeling, yet their prohibitively high computational complexity and resource consumption limit deployment in edge computing. In this paper, we propose an FPGA-based BNN inference accelerator that optimizes critical mo...

Xiao-Tao Jia, Bing-Yue Zhang, Zigui Wu et al. · IEEE Transactions on Circuit... · 1 citation

#machine learning Preprint Sep 2026

MegaGraph: Towards Efficient Training of Large-Scale Graph Transformers with Automated Hybrid Parallelism

Evaluations demonstrate that MegaGraph enables training on large-scale graphs where state-of-the-art baselines fail due to out-of-memory (OOM) errors, and achieves up to 4.51 times training speedup while maintaining model accuracy.

Tong Qiao, Ao Zhou, Ying-Jie Qi et al. · 0 citations

Open access Aug 2026

EcoVLA: Energy-Efficient Device-Edge Co-inference for Vision-Language-Action Models Under Real-Time Constraints

Vision-Language-Action (VLA) models have emerged as a promising foundation for Embodied AI, but their high inference cost poses significant challenges for deployment in robotic systems. In practice, on-device inference is constrained by limited compute capacity and energy budgets, struggling to simultaneously satisfy r...

Ao Zhou, Bo Dai, Le Yu et al. · Advanced Parallel Programmin... · 1 citation