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Zixun Lan
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2020 – today
- 2024
- [j3]Zixun Lan, Zuo Zeng, Binjie Hong, Zhenfu Liu, Fei Ma:
RCsearcher: Reaction center identification in retrosynthesis via deep Q-learning. Pattern Recognit. 150: 110318 (2024) - [j2]Zixun Lan, Binjie Hong, Ye Ma, Fei Ma:
More Interpretable Graph Similarity Computation via Maximum Common Subgraph Inference. IEEE Trans. Knowl. Data Eng. 36(11): 6588-6599 (2024) - [i6]Zixun Lan, Binjie Hong, Jiajun Zhu, Zuo Zeng, Zhenfu Liu, Limin Yu, Fei Ma:
Retrosynthesis Prediction via Search in (Hyper) Graph. CoRR abs/2402.06772 (2024) - 2023
- [j1]Zixun Lan, Ye Ma, Limin Yu, Linglong Yuan, Fei Ma:
AEDNet: Adaptive Edge-Deleting Network For Subgraph Matching. Pattern Recognit. 133: 109033 (2023) - [c3]Zixun Lan, Limin Yu, Linglong Yuan, Zili Wu, Qiang Niu, Fei Ma:
Sub-GMN: The Neural Subgraph Matching Network Model. CISP-BMEI 2023: 1-7 - [c2]Jiajun Zhu, Binjie Hong, Zixun Lan, Fei Ma:
Single-step Retrosynthesis via Reaction Center and Leaving Groups Prediction. CISP-BMEI 2023: 1-5 - [i5]Zixun Lan, Zuo Zeng, Binjie Hong, Zhenfu Liu, Fei Ma:
RCsearcher: Reaction Center Identification in Retrosynthesis via Deep Q-Learning. CoRR abs/2301.12071 (2023) - [i4]Jiajun Zhu, Zichuan Yang, Binjie Hong, Jiacheng Song, Jiwei Wang, Tianhao Chen, Shuilan Yang, Zixun Lan, Fei Ma:
Use neural networks to recognize students' handwritten letters and incorrect symbols. CoRR abs/2309.06221 (2023) - 2022
- [i3]Zixun Lan, Binjie Hong, Ye Ma, Fei Ma:
More Interpretable Graph Similarity Computation via Maximum Common Subgraph Inference. CoRR abs/2208.04580 (2022) - [i2]Zixun Lan, Ye Ma, Limin Yu, Linglong Yuan, Fei Ma:
AEDNet: Adaptive Edge-Deleting Network For Subgraph Matching. CoRR abs/2211.04033 (2022) - 2021
- [c1]Ye Ma, Zixun Lan, Lu Zong, Kaizhu Huang:
Global-aware Beam Search for Neural Abstractive Summarization. NeurIPS 2021: 16545-16557 - [i1]Zixun Lan, Limin Yu, Linglong Yuan, Zili Wu, Qiang Niu, Fei Ma:
Sub-GMN: The Subgraph Matching Network Model. CoRR abs/2104.00186 (2021)
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last updated on 2024-11-06 20:27 CET by the dblp team
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