Deep retrosynthetic reaction prediction using local reactivity and global attention

2021年8月5日 · Our model shows a promising 89.5 and 99.2% round-trip accuracy at top-1 and top-5 predictions for the USPTO-50K dataset containing 50 016 reactions. We further …

S Chen and Y Jung, “Deep Retrosynthetic Reaction Prediction using Local Reactivity and Global Attention”, JACS Au 2021; Conference - Talks. S Chen and Y Jung,”Automatic generation of …

Shuan Chen Korea Advanced Institute of Science and Technology: Daejeon, Daejeon, KR 2018-08 to 2020-07 | Master's degree (Chemical and biomolecular engineering)

2021年8月5日 · Segler and Waller proposed a hybrid neural-symbolic approach to predict the retrosynthesis pathway using either hand-coded or automatically extracted rules by a deep …

Segler and Waller11 proposed a hybrid neural-symbolic approach to predict the retrosynthesis pathway using either hand-coded or automatically extracted rules by a deep neural network.

In this study, deep learning models based on hyperspectral data and time-series phenotypes from the high-throughput plant phenotyping (HTPP) platform were proposed to predict quality …

Shuan Chen Affiliation Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea

Shuan Chen, Yousung Jung: A generalized-template-based graph neural network for accurate organic reactivity prediction. Nat. Mac. Intell. 4 (9): 772-780 (2022)

2023年8月6日 · This study describes the initial development of a deep learning algorithm, ROP.AI, trained to automatically diagnose ROP plus disease. Our results have shown that a …