Marwin Segler

Principal Researcher

Publications

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- Accurate Chemistry Collection: Coupled cluster atomization energies for broad chemical space
  
  Sebastian Ehlert, Jan Hermann, Thijs Vogels, Victor Garcia Satorras, Stephanie Lanius, Marwin Segler, Derk Kooi, Kenji Takeda, Chin-Wei Huang, Giulia Luise, Rianne van den Berg, Paola Gori-Giorgi, Amir Karton
  
  June 2025
  
  PDF Preprint Video Download
- Nature Language Model: Deciphering the Language of Nature for Scientific Discovery
  
  Yingce Xia, Peiran Jin, Shufang Xie, Liang He, Chuan Cao, Renqian Luo, Guoqing Liu, Yue Wang, Zequn Liu, Yuan-Jyue Chen, Yuan Chen, Zekun Guo, Yeqi Bai, Pan Deng, Yaosen Min, Zi‐Ang Lu, Hongxia Hao, Han Yang, Jielan Li, Chang Liu, Jia Zhang, Jian-Bo Zhu, Ke-Ming Wu, Wei Zhang, Kaiyuan Gao, Qizhi Pei, Qian Wang, Xixian Liu, Yanting Li, Houtian Zhu, Yeqing Lu, Mingqian Ma, Zun Wang, Tian Xie, Krzysztof Maziarz, Marwin H. S. Segler, Zhao Yang, Zi-wei Chen, Yu Shi, Shuxin Zheng, Lijun Wu, Chen Hu, Peggy Dai, Tiemin Liu, Hai-Long Liu, Tao Qin
  
  March 2025
  
  Preprint
- Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases
  
  Krzysztof Maziarz, Guoqing Liu, Hubert Misztela, Aleksei Kornev, Piotr Gaiński, Holger Hoefling, Mike Fortunato, Rishi Gupta, Marwin Segler
  
  December 2024
  
  Publication Video
- Re-evaluating Retrosynthesis Algorithms with Syntheseus
  
  Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gaiński, Philipp Seidl, Marwin Segler
  
  Faraday Discussions | October 2023
  
  DOI Publication Publication
- Retro-fallback: retrosynthetic planning in an uncertain world
  
  Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Jose Miguel Hernandez-Lobato, Marwin Segler
  
  ICLR 2024 | October 2023
  
  DOI PDF
- Retrosynthetic Planning with Dual Value Networks
  
  Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu
  
  ICML 2023 | June 2023
  
  Publication
- Re-Evaluating Chemical Synthesis Planning Algorithms
  
  Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Guoqing Liu, Marwin Segler
  
  NeurIPS 2022 (AI for Science: Progress and Promises Workshop) | December 2022
  
  Publication PDF Project
- Learning to Extend Molecular Scaffolds with Structural Motifs
  
  Krzysztof Maziarz, Henry Jackson-Flux, Pashmina Cameron, Finton Sirockin, Nadine Schneider, Nikolaus Stiefl, Marwin Segler, Marc Brockschmidt
  
  ICLR 2022 | April 2022
  
  Publication Github Project
- FS-Mol: A Few-Shot Learning Dataset of Molecules
  
  Megan Stanley, John Bronskill, Krzysztof Maziarz, Hubert Misztela, Jessica Lanini, Marwin Segler, Nadine Schneider, Marc Brockschmidt
  
  NeurIPS 2021 | December 2021
  
  Publication Github Project

- Accurate Chemistry Collection: Coupled cluster atomization energies for broad chemical space
  
  Sebastian Ehlert, Jan Hermann, Thijs Vogels, Victor Garcia Satorras, Stephanie Lanius, Marwin Segler, Derk Kooi, Kenji Takeda, Chin-Wei Huang, Giulia Luise, Rianne van den Berg, Paola Gori-Giorgi, Amir Karton
  
  June 2025
  
  PDF Preprint Video Download
- Nature Language Model: Deciphering the Language of Nature for Scientific Discovery
  
  Yingce Xia, Peiran Jin, Shufang Xie, Liang He, Chuan Cao, Renqian Luo, Guoqing Liu, Yue Wang, Zequn Liu, Yuan-Jyue Chen, Yuan Chen, Zekun Guo, Yeqi Bai, Pan Deng, Yaosen Min, Zi‐Ang Lu, Hongxia Hao, Han Yang, Jielan Li, Chang Liu, Jia Zhang, Jian-Bo Zhu, Ke-Ming Wu, Wei Zhang, Kaiyuan Gao, Qizhi Pei, Qian Wang, Xixian Liu, Yanting Li, Houtian Zhu, Yeqing Lu, Mingqian Ma, Zun Wang, Tian Xie, Krzysztof Maziarz, Marwin H. S. Segler, Zhao Yang, Zi-wei Chen, Yu Shi, Shuxin Zheng, Lijun Wu, Chen Hu, Peggy Dai, Tiemin Liu, Hai-Long Liu, Tao Qin
  
  March 2025
  
  Preprint
- Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases
  
  Krzysztof Maziarz, Guoqing Liu, Hubert Misztela, Aleksei Kornev, Piotr Gaiński, Holger Hoefling, Mike Fortunato, Rishi Gupta, Marwin Segler
  
  December 2024
  
  Publication Video
- Re-evaluating Retrosynthesis Algorithms with Syntheseus
  
  Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gaiński, Philipp Seidl, Marwin Segler
  
  Faraday Discussions | October 2023
  
  DOI Publication Publication
- Retro-fallback: retrosynthetic planning in an uncertain world
  
  Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Jose Miguel Hernandez-Lobato, Marwin Segler
  
  ICLR 2024 | October 2023
  
  DOI PDF
- Retrosynthetic Planning with Dual Value Networks
  
  Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu
  
  ICML 2023 | June 2023
  
  Publication
- Re-Evaluating Chemical Synthesis Planning Algorithms
  
  Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Guoqing Liu, Marwin Segler
  
  NeurIPS 2022 (AI for Science: Progress and Promises Workshop) | December 2022
  
  Publication PDF Project
- Learning to Extend Molecular Scaffolds with Structural Motifs
  
  Krzysztof Maziarz, Henry Jackson-Flux, Pashmina Cameron, Finton Sirockin, Nadine Schneider, Nikolaus Stiefl, Marwin Segler, Marc Brockschmidt
  
  ICLR 2022 | April 2022
  
  Publication Github Project
- FS-Mol: A Few-Shot Learning Dataset of Molecules
  
  Megan Stanley, John Bronskill, Krzysztof Maziarz, Hubert Misztela, Jessica Lanini, Marwin Segler, Nadine Schneider, Marc Brockschmidt
  
  NeurIPS 2021 | December 2021
  
  Publication Github Project

- Accurate Chemistry Collection: Coupled cluster atomization energies for broad chemical space
  
  Sebastian Ehlert, Jan Hermann, Thijs Vogels, Victor Garcia Satorras, Stephanie Lanius, Marwin Segler, Derk Kooi, Kenji Takeda, Chin-Wei Huang, Giulia Luise, Rianne van den Berg, Paola Gori-Giorgi, Amir Karton
  
  June 2025
  
  PDF Preprint Video Download
- Nature Language Model: Deciphering the Language of Nature for Scientific Discovery
  
  Yingce Xia, Peiran Jin, Shufang Xie, Liang He, Chuan Cao, Renqian Luo, Guoqing Liu, Yue Wang, Zequn Liu, Yuan-Jyue Chen, Yuan Chen, Zekun Guo, Yeqi Bai, Pan Deng, Yaosen Min, Zi‐Ang Lu, Hongxia Hao, Han Yang, Jielan Li, Chang Liu, Jia Zhang, Jian-Bo Zhu, Ke-Ming Wu, Wei Zhang, Kaiyuan Gao, Qizhi Pei, Qian Wang, Xixian Liu, Yanting Li, Houtian Zhu, Yeqing Lu, Mingqian Ma, Zun Wang, Tian Xie, Krzysztof Maziarz, Marwin H. S. Segler, Zhao Yang, Zi-wei Chen, Yu Shi, Shuxin Zheng, Lijun Wu, Chen Hu, Peggy Dai, Tiemin Liu, Hai-Long Liu, Tao Qin
  
  March 2025
  
  Preprint
- Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases
  
  Krzysztof Maziarz, Guoqing Liu, Hubert Misztela, Aleksei Kornev, Piotr Gaiński, Holger Hoefling, Mike Fortunato, Rishi Gupta, Marwin Segler
  
  December 2024
  
  Publication Video
- Re-evaluating Retrosynthesis Algorithms with Syntheseus
  
  Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gaiński, Philipp Seidl, Marwin Segler
  
  Faraday Discussions | October 2023
  
  DOI Publication Publication
- Retro-fallback: retrosynthetic planning in an uncertain world
  
  Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Jose Miguel Hernandez-Lobato, Marwin Segler
  
  ICLR 2024 | October 2023
  
  DOI PDF
- Retrosynthetic Planning with Dual Value Networks
  
  Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu
  
  ICML 2023 | June 2023
  
  Publication
- Re-Evaluating Chemical Synthesis Planning Algorithms
  
  Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Guoqing Liu, Marwin Segler
  
  NeurIPS 2022 (AI for Science: Progress and Promises Workshop) | December 2022
  
  Publication PDF Project
- Learning to Extend Molecular Scaffolds with Structural Motifs
  
  Krzysztof Maziarz, Henry Jackson-Flux, Pashmina Cameron, Finton Sirockin, Nadine Schneider, Nikolaus Stiefl, Marwin Segler, Marc Brockschmidt
  
  ICLR 2022 | April 2022
  
  Publication Github Project
- FS-Mol: A Few-Shot Learning Dataset of Molecules
  
  Megan Stanley, John Bronskill, Krzysztof Maziarz, Hubert Misztela, Jessica Lanini, Marwin Segler, Nadine Schneider, Marc Brockschmidt
  
  NeurIPS 2021 | December 2021
  
  Publication Github Project

Marwin Segler

Publications

Accurate Chemistry Collection: Coupled cluster atomization energies for broad chemical space

Nature Language Model: Deciphering the Language of Nature for Scientific Discovery

Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases

Re-evaluating Retrosynthesis Algorithms with Syntheseus

Retro-fallback: retrosynthetic planning in an uncertain world

Retrosynthetic Planning with Dual Value Networks

Re-Evaluating Chemical Synthesis Planning Algorithms

Learning to Extend Molecular Scaffolds with Structural Motifs

FS-Mol: A Few-Shot Learning Dataset of Molecules

Accurate Chemistry Collection: Coupled cluster atomization energies for broad chemical space

Nature Language Model: Deciphering the Language of Nature for Scientific Discovery

Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases

Re-evaluating Retrosynthesis Algorithms with Syntheseus

Retro-fallback: retrosynthetic planning in an uncertain world

Retrosynthetic Planning with Dual Value Networks

Re-Evaluating Chemical Synthesis Planning Algorithms

Learning to Extend Molecular Scaffolds with Structural Motifs

FS-Mol: A Few-Shot Learning Dataset of Molecules

Accurate Chemistry Collection: Coupled cluster atomization energies for broad chemical space

Nature Language Model: Deciphering the Language of Nature for Scientific Discovery

Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases

Re-evaluating Retrosynthesis Algorithms with Syntheseus

Retro-fallback: retrosynthetic planning in an uncertain world

Retrosynthetic Planning with Dual Value Networks

Re-Evaluating Chemical Synthesis Planning Algorithms

Learning to Extend Molecular Scaffolds with Structural Motifs

FS-Mol: A Few-Shot Learning Dataset of Molecules

Contact Marwin Segler

Microsoft Research AI for Science

Microsoft Research Lab – Cambridge