From Atomic Scale Ordering to Mesoscale Spatial Patterns in Surface Reactions: A Heterogeneous Coupled Lattice-Gas Simulation Approach. - Dajiang Liu; James W. Evans (Multiscale Model. Simul., 2005)

Mapping Optimization of Affine Loop Nests for Reconfigurable Computing Architecture. - Dajiang Liu; Shouyi Yin; Chongyong Yin; Leibo Liu; Shaojun Wei (IEICE Trans. Inf. Syst., 2012)

Polyhedral model based mapping optimization of loop nests for CGRAs. - Dajiang Liu; Shouyi Yin; Leibo Liu; Shaojun Wei (DAC, 2013)

Affine transformations for communication and reconfiguration optimization of loops on CGRAs. - Dajiang Liu; Shouyi Yin; Leibo Liu; Shaojun Wei (ISCAS, 2013)

Affine Transformations for Communication and Reconfiguration Optimization of Mapping Loop Nests on CGRAs. - Shouyi Yin; Dajiang Liu; Leibo Liu; Shaojun Wei (IEICE Trans. Inf. Syst., 2013)

Exploiting Outer Loop Parallelism of Nested Loop on Coarse-Grained Reconfigurable Architectures. - Dajiang Liu; Shouyi Yin; Leibo Liu; Shaojun Wei (FCCM, 2014)

RAREMETAL: fast and powerful meta-analysis for rare variants. - Shuang Feng; Dajiang Liu; Xiaowei Zhan; Mary Kate Wing; Gonçalo R. Abecasis (Bioinform., 2014)

Joint affine transformation and loop pipelining for mapping nested loop on CGRAs. - Shouyi Yin; Dajiang Liu; Leibo Liu; Shaojun Wei; Yike Guo (DATE, 2015)

Mapping Multi-Level Loop Nests onto CGRAs Using Polyhedral Optimizations. - Dajiang Liu; Shouyi Yin; Leibo Liu; Shaojun Wei (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2015)

Optimizing Spatial Mapping of Nested Loop for Coarse-Grained Reconfigurable Architectures. - Dajiang Liu; Shouyi Yin; Yu Peng; Leibo Liu; Shaojun Wei (IEEE Trans. Very Large Scale Integr. Syst., 2015)

Joint Modulo Scheduling and Vdd Assignment for Loop Mapping on Dual- Vdd CGRAs. - Shouyi Yin; Jiangyuan Gu; Dajiang Liu; Leibo Liu; Shaojun Wei (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2016)

Improving Nested Loop Pipelining on Coarse-Grained Reconfigurable Architectures. - Shouyi Yin; Dajiang Liu; Yu Peng; Leibo Liu; Shaojun Wei (IEEE Trans. Very Large Scale Integr. Syst., 2016)

Memory-Aware Loop Mapping on Coarse-Grained Reconfigurable Architectures. - Shouyi Yin; Xianqing Yao; Dajiang Liu; Leibo Liu; Shaojun Wei (IEEE Trans. Very Large Scale Integr. Syst., 2016)

Learning Convolutional Neural Networks for Data-Flow Graph Mapping on Spatial Programmable Architectures (Abstract Only). - Shouyi Yin; Dajiang Liu; Lifeng Sun; Xinhan Lin; Leibo Liu; Shaojun Wei (FPGA, 2017)

DFGNet: Mapping dataflow graph onto CGRA by a deep learning approach. - Shouyi Yin; Dajiang Liu; Lifeng Sun; Leibo Liu; Shaojun Wei (ISCAS, 2017)

Conflict-Free Loop Mapping for Coarse-Grained Reconfigurable Architecture with Multi-Bank Memory. - Shouyi Yin; Xianqing Yao; Tianyi Lu; Dajiang Liu; Jiangyuan Gu; Leibo Liu; Shaojun Wei (IEEE Trans. Parallel Distributed Syst., 2017)

CurveCluster: Automated Recognition of Hard Landing Patterns Based on QAR Curve Clustering. - Xu Li 014; Jiaxing Shang; Linjiang Zheng; Dajiang Liu; Lin Qi; Liu Liu (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI, 2019)

Data-Flow Graph Mapping Optimization for CGRA With Deep Reinforcement Learning. - Dajiang Liu; Shouyi Yin; Guojie Luo; Jiaxing Shang; Leibo Liu; Shaojun Wei; Yong Feng 002; Shangbo Zhou (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2019)

A Deep Sequence-to-Sequence Method for Aircraft Landing Speed Prediction Based on QAR Data. - Zongwei Kang; Jiaxing Shang; Yong Feng 002; Linjiang Zheng; Dajiang Liu; Baohua Qiang; Ran Wei (WISE (2), 2020)

FRWCAE: joint faster-RCNN and Wasserstein convolutional auto-encoder for instance retrieval. - Yiyang Zhang; Yong Feng 002; Dajiang Liu; Jiaxing Shang; Baohua Qiang (Appl. Intell., 2020)

Adversarial Metric Learning with Naive Similarity Discriminator. - Yi-Ze Le; Yong Feng 002; Dajiang Liu; Baohua Qiang (IEICE Trans. Inf. Syst., 2020)

Polyhedral-based Pipelining of Imperfectly-Nested Loop for CGRAs. - Dajiang Liu; Ting Liu; Xingyu Mo; Jiaxing Shang; Shouyi Yin (ICCAD, 2021)

Dynamic Convolution Pruning Using Pooling Characteristic in Convolution Neural Networks. - Yu Zhang; Dajiang Liu; Yongkang Xing (ICONIP (5), 2021)

BaCIM: Balanced Competitive Influence Maximization based on Blocked Reverse Influence Sampling. - Shuang Gao; Wu Xie; Jiaxing Shang; Dajiang Liu; Baohua Qiang (MDM, 2021)

Accepted Influence Maximization under Linear Threshold Model on Large-Scale Social Networks. - Xiaojuan Yang; Jiaxing Shang; Linjiang Zheng; Dajiang Liu; Shu Fu; Baohua Qiang (TrustCom, 2021)

RNe2Vec: information diffusion popularity prediction based on repost network embedding. - Jiaxing Shang; Shuo Huang; Dingyang Zhang; Zixuan Peng; Dajiang Liu; Yong Li; Lexi Xu (Computing, 2021)

HMSG: Heterogeneous Graph Neural Network based on Metapath Subgraph Learning. - Xinjun Cai; Jiaxing Shang; Fei Hao 001; Dajiang Liu; Linjiang Zheng (CoRR, 2021)

A dynamic critical path method for project scheduling based on a generalised fuzzy similarity. - Dajiang Liu; Changming Hu (J. Oper. Res. Soc., 2021)

CollaborateCas: Popularity Prediction of Information Cascades Based on Collaborative Graph Attention Networks. - Xianren Zhang; Jiaxing Shang; Xueqi Jia; Dajiang Liu; Fei Hao 001; Zhiqing Zhang (DASFAA (1), 2022)

Towards Energy-Efficient CGRAs via Stochastic Computing. - Bo Wang; Rong Zhu; Jiaxing Shang; Dajiang Liu (DATE, 2022)

RF-CGRA: A Routing-Friendly CGRA with Hierarchical Register Chains. - Rong Zhu; Bo Wang; Dajiang Liu (DATE, 2022)

Towards High-Quality CGRA Mapping with Graph Neural Networks and Reinforcement Learning. - Yan Zhuang; Zhihao Zhang; Dajiang Liu (ICCAD, 2022)

ConCas: Cascade Popularity Prediction Based on Topic-Aware Graph Contrastive Learning. - Chen Ling; Xianren Zhang; Jiaxing Shang; Dajiang Liu; Yong Li; Wu Xie; Baohua Qiang (KSEM (1), 2022)

Social Information Popularity Prediction based on Heterogeneous Diffusion Attention Network. - Xueqi Jia; Jiaxing Shang; Linjiang Zheng; Dajiang Liu; Weiwei Cao; Hong Sun (SEKE, 2022)

IM2Vec: Representation learning-based preference maximization in geo-social networks. - Ziwei Jin; Jiaxing Shang; Wancheng Ni; Liang Zhao 004; Dajiang Liu; Baohua Qiang; Wu Xie; Geyong Min (Inf. Sci., 2022)

HeDAN: Heterogeneous diffusion attention network for popularity prediction of online content. - Xueqi Jia; Jiaxing Shang; Dajiang Liu; Haidong Zhang; Wancheng Ni (Knowl. Based Syst., 2022)

Towards High-Bandwidth-Utilization SpMV on FPGAs via Partial Vector Duplication. - Bowen Liu; Dajiang Liu (ASP-DAC, 2023)

Optimizing Data Reuse for CGRA Mapping Using Polyhedral-based Loop Transformations. - Liao Huang; Dajiang Liu (DAC, 2023)

DARIC: A Data Reuse-Friendly CGRA for Parallel Data Access via Elastic FIFOs. - Dajiang Liu; Di Mou; Rong Zhu; Yan Zhuang; Jiaxing Shang; Jiang Zhong; Shouyi Yin (DAC, 2023)

Optimizing Memory Allocation for Multi-Subgraph Mapping on Spatial Accelerators. - Lei Lei; Decai Pan; Dajiang Liu; Peng Ouyang; Xueliang Du (SYSTOR, 2023)

HMSG: Heterogeneous graph neural network based on Metapath SubGraph learning. - Mengya Guan; Xinjun Cai; Jiaxing Shang; Fei Hao 001; Dajiang Liu; Xianlong Jiao; Wancheng Ni (Knowl. Based Syst., 2023)

PMP: Pattern Morphing-based Memory Partitioning in High-Level Synthesis. - Dajiang Liu; Decai Pan; Xiao Xiong; Jiaxing Shang; Shouyi Yin (DAC, 2024)

Optimizing Imperfectly-Nested Loop Mapping on CGRAs via Polyhedral-Guided Flattening. - Xingyu Mo; Yawen Li; Dajiang Liu (DATE, 2024)

E2EMap: End-to-End Reinforcement Learning for CGRA Compilation via Reverse Mapping. - Dajiang Liu; Yuxin Xia; Jiaxing Shang; Jiang Zhong; Peng Ouyang; Shouyi Yin (HPCA, 2024)

DISC: Exploiting Data Parallelism of Non-Stencil Computations on CGRAs via Dynamic Iteration Scheduling. - Yue Liang 004; Di Mou; Dajiang Liu (ICCAD, 2024)

BALQUE: Batch active learning by querying unstable examples with calibrated confidence. - Yincheng Han; Dajiang Liu; Jiaxing Shang; Linjiang Zheng; Jiang Zhong; Weiwei Cao; Hong Sun; Wu Xie (Pattern Recognit., 2024)

ARIS: Efficient Admitted Influence Maximizing in Large-Scale Networks Based on Valid Path Reverse Influence Sampling. - Xiaojuan Yang; Jiaxing Shang; Qinghong Hu; Dajiang Liu (IEEE Trans. Emerg. Top. Comput., 2024)

SC-CGRA: An Energy-Efficient CGRA Using Stochastic Computing. - Di Mou; Bo Wang; Dajiang Liu (IEEE Trans. Parallel Distributed Syst., 2024)

IMTCN: An Interpretable Flight Safety Analysis and Prediction Model Based on Multi-Scale Temporal Convolutional Networks. - Xu Li 014; Jiaxing Shang; Linjiang Zheng; Qixing Wang; Dajiang Liu; Xiaodong Liu; Fan Li; Weiwei Cao; Hong Sun (IEEE Trans. Intell. Transp. Syst., 2024)

DynaX: Sparse Attention Acceleration with Dynamic X: M Fine-Grained Structured Pruning. - Xiao Xiong; Zhaorui Chen; Yue Liang 004; Minghao Tian; Jiaxing Shang; Jiang Zhong; Dajiang Liu (ASPLOS (2), 2025)

SDVD: Self-supervised dual-view modeling of user and cascade dynamics for information diffusion prediction. - Haoyu Xiong; Jiaxing Shang; Fei Hao 001; Dajiang Liu; Geyong Min (Knowl. Based Syst., 2025)

Optimizing Data Reuse for Loop Mapping on CGRAs With Joint Affine and Nonaffine Transformations. - Liao Huang; Yue Chen; Dajiang Liu (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)

CoSpMV: Towards Agile Software and Hardware Co-Design for SpMV Computation. - Minghao Tian; Yue Liang 004; Bowen Liu; Dajiang Liu (IEEE Trans. Computers, 2025)