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Olaf Wiest
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2020 – today
- 2024
- [j1]Olaf Wiest
, Christoph Alexander Bauer, Paul Helquist
Finding Relevant Retrosynthetic Disconnections for Stereocontrolled Reactions. J. Chem. Inf. Model. 64(15): 5796-5805 (2024) - [c7]Xiaobao Huang
Application of Large Language Models in Chemistry Reaction Data Extraction and Cleaning. CIKM 2024: 3797-3801 - [c6]Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang:
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. ICLR 2024 - [c5]Taicheng Guo, Xiuying Chen, Yaqi Wang, Ruidi Chang, Shichao Pei, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang:
Large Language Model Based Multi-agents: A Survey of Progress and Challenges. IJCAI 2024: 8048-8057 - [c4]Yihong Ma
Are we Making Much Progress? Revisiting Chemical Reaction Yield Prediction from an Imbalanced Regression Perspective. WWW (Companion Volume) 2024: 790-793 - [i8]Taicheng Guo, Xiuying Chen, Yaqi Wang, Ruidi Chang, Shichao Pei, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang:
Large Language Model based Multi-Agents: A Survey of Progress and Challenges. CoRR abs/2402.01680 (2024) - [i7]Yihong Ma, Xiaobao Huang, Bozhao Nan
Are we making much progress? Revisiting chemical reaction yield prediction from an imbalanced regression perspective. CoRR abs/2402.05971 (2024) - [i6]Khiem Le, Zhichun Guo, Kaiwen Dong, Xiaobao Huang, Bozhao Nan, Roshni G. Iyer, Xiangliang Zhang, Olaf Wiest, Wei Wang, Nitesh V. Chawla:
MolX: Enhancing Large Language Models for Molecular Learning with A Multi-Modal Extension. CoRR abs/2406.06777 (2024) - 2023
- [c3]Zhichun Guo, Kehan Guo, Bozhao Nan, Yijun Tian, Roshni G. Iyer, Yihong Ma, Olaf Wiest, Xiangliang Zhang, Wei Wang, Chuxu Zhang, Nitesh V. Chawla:
Graph-based Molecular Representation Learning. IJCAI 2023: 6638-6646 - [c2]Taicheng Guo, Kehan Guo, Bozhao Nan, Zhenwen Liang, Zhichun Guo, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang:
What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks. NeurIPS 2023 - [i5]Taicheng Guo, Kehan Guo, Bozhao Nan
What indeed can GPT models do in chemistry? A comprehensive benchmark on eight tasks. CoRR abs/2305.18365 (2023) - [i4]Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. CoRR abs/2310.00115 (2023) - [i3]Taicheng Guo, Changsheng Ma, Xiuying Chen, Bozhao Nan
Modeling non-uniform uncertainty in Reaction Prediction via Boosting and Dropout. CoRR abs/2310.04674 (2023) - 2022
- [i2]Zhichun Guo, Bozhao Nan
Graph-based Molecular Representation Learning. CoRR abs/2207.04869 (2022) - 2021
- [c1]Zhichun Guo, Chuxu Zhang, Wenhao Yu
Few-Shot Graph Learning for Molecular Property Prediction. WWW 2021: 2559-2567 - [i1]Zhichun Guo, Chuxu Zhang, Wenhao Yu, John Herr, Olaf Wiest, Meng Jiang, Nitesh V. Chawla:
Few-Shot Graph Learning for Molecular Property Prediction. CoRR abs/2102.07916 (2021)
Coauthor Index
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