Olaf Wiest

According to our database, Olaf Wiest authored at least 12 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Finding Relevant Retrosynthetic Disconnections for Stereocontrolled Reactions.

Olaf Wiest, Christoph Alexander Bauer, Paul Helquist, Per-Ola Norrby, Samuel Genheden

J. Chem. Inf. Model., 2024

MolX: Enhancing Large Language Models for Molecular Learning with A Multi-Modal Extension.

Khiem Le, Zhichun Guo, Kaiwen Dong, Xiaobao Huang, Bozhao Nan, Roshni G. Iyer, Xiangliang Zhang, Olaf Wiest, Wei Wang, Nitesh V. Chawla

CoRR, 2024

Are we Making Much Progress? Revisiting Chemical Reaction Yield Prediction from an Imbalanced Regression Perspective.

Yihong Ma, Xiaobao Huang, Bozhao Nan, Nuno Moniz, Xiangliang Zhang, Olaf Wiest, Nitesh V. Chawla

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Large Language Model Based Multi-agents: A Survey of Progress and Challenges.

Taicheng Guo, Xiuying Chen, Yaqi Wang, Ruidi Chang, Shichao Pei, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks.

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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Application of Large Language Models in Chemistry Reaction Data Extraction and Cleaning.

Xiaobao Huang, Mihir Surve, Yuhan Liu, Tengfei Luo, Olaf Wiest, Xiangliang Zhang, Nitesh V. Chawla

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Modeling non-uniform uncertainty in Reaction Prediction via Boosting and Dropout.

Taicheng Guo, Changsheng Ma, Xiuying Chen, Bozhao Nan, Kehan Guo, Shichao Pei, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang

CoRR, 2023

What indeed can GPT models do in chemistry? A comprehensive benchmark on eight tasks.

Taicheng Guo, Kehan Guo, Bozhao Nan, Zhengwen Liang, Zhichun Guo, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang

CoRR, 2023

What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks.

Taicheng Guo, Kehan Guo, Bozhao Nan, Zhenwen Liang, Zhichun Guo, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Graph-based Molecular Representation Learning.

Zhichun Guo, Kehan Guo, Bozhao Nan, Yijun Tian, Roshni G. Iyer, Yihong Ma, Olaf Wiest, Xiangliang Zhang, Wei Wang, Chuxu Zhang, Nitesh V. Chawla

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

Graph-based Molecular Representation Learning.

Zhichun Guo, Bozhao Nan, Yijun Tian, Olaf Wiest, Chuxu Zhang, Nitesh V. Chawla

CoRR, 2022

2021

Few-Shot Graph Learning for Molecular Property Prediction.

Zhichun Guo, Chuxu Zhang, Wenhao Yu, John Herr, Olaf Wiest, Meng Jiang, Nitesh V. Chawla

Proceedings of the WWW '21: The Web Conference 2021, 2021