袁之航简介

袁之航于2017年获得北京大学药学院学士学位,于2022年获得北京大学计算机学院博士学位。研究方向为:神经网络压缩加速、软硬件协同设计、存算一体AI处理器。袁之航累计参与8款AI芯片的研发。当前在存算一体芯片创业公司后摩智能工作。

部分发表论文

  • Han Y, Yuan Z, Pu Y, et al. Latency-aware Spatial-wise Dynamic Networks, NeurIPS 2022.
  • Li X, Yuan Z, Guan Y, et al. Flatfish: a Reinforcement Learning Approach for Application-Aware Address Mapping[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2022.
  • Li X, Bing Z, Guang Y, et al. Enabling High-Quality Uncertainty Quantification in a PIM Designed for Bayesian Neural Network. HPCA, 2022.
  • Yuan Z, Xue C, Chen Y, et al. PTQ4ViT: Post-Training Quantization Framework for Vision Transformers[J]. European Conference on Computer Vision (ECCV), 2022.
  • Yuan Z, Chen Y, Xue C, et al. PTQ-SL: Exploring the Sub-layerwise Post-training Quantization[J]. arXiv preprint arXiv:2110.07809, 2021.
  • Yuan Z, Jingze L, Xingchen L, et al. NAS4RRAM: Neural Network Architecture Search for Inference on RRAM-based Accelerators[J]. SCIENCE CHINA Information Sciences, 2021.
  • Yuan Z, Wu B, Sun G, et al. S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search[C]. European Conference on Computer Vision (ECCV), 2020. (oral)
  • Yuan Z, Liu X, Wu B, et al. ENAS4D: Efficient Multi-stage CNN Architecture Search for Dynamic Inference[J]. arXiv preprint, 2020.
  • Guan Y, Sun G, Yuan Z, et al. Crane: Mitigating Accelerator Under-utilization Caused by Sparsity Irregularities in CNNs[J]. IEEE Transactions on Computers (TC), 2020.
  • Guan Y, Yuan Z, Sun G, et al. FPGA-based accelerator for long short-term memory recurrent neural networks[C]. Asia and South Pacific Design Automation Conference (ASP-DAC), 2017.
  • Wu B, Liu Z, Yuan Z, et al. Reducing overfitting in deep convolutional neural networks using redundancy regularizer[C]. International Conference on Artificial Neural Networks (ICANN), 2017.
Your browser is out-of-date!

Update your browser to view this website correctly. Update my browser now

×