Marwin H. S. Segler

42 papers A* 7Journal 30Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Scientific Reasoning Model for Organic Synthesis Procedure Generation. CoRR Guoqing Liu, Junren Li, Zihan Zhao, Eray Inanc, Krzysztof Maziarz, José Garrido Torres, Victor Garcia Satorras, Shoko Ueda, Christopher M. Bishop, Marwin H. S. Segler
2025	J	`jnl`	Challenging reaction prediction models to generalize to novel chemistry. CoRR John Bradshaw, Anji Zhang, Babak A. Mahjour, David E. Graff, Marwin H. S. Segler, Connor W. Coley
2025	J	`jnl`	Diverse and feasible retrosynthesis using GFlowNets. Inf. Sci. Piotr Gainski, Michal Koziarski, Krzysztof Maziarz, Marwin H. S. Segler, Jacek Tabor, Marek Smieja
2025	J	`jnl`	NatureLM: Deciphering the Language of Nature for Scientific Discovery. CoRR Yingce Xia, Peiran Jin, Shufang Xie, Liang He, Chuan Cao, Renqian Luo, Guoqing Liu, Yue Wang, Zequn Liu, Yuan-Jyue Chen, Zekun Guo, Yeqi Bai, Pan Deng, Yaosen Min, Ziheng Lu, Hongxia Hao, Han Yang, Jielan Li, Chang Liu, Jia Zhang, Jianwei Zhu, Kehan 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, Zilong Chen, Yu Shi, Shuxin Zheng, Lijun Wu, Chen Hu, Peggy Dai, Tie-Yan Liu, Haiguang Liu, Tao Qin
2025	A*	`conf`	SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints. ICLR Miruna T. Cretu, Charles Harris, Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Bruno E. Correia, Julien Roy, Emmanuel Bengio, Pietro Lio
2025	J	`jnl`	UniGenX: Unified Generation of Sequence and Structure with Autoregressive Diffusion. CoRR Gongbo Zhang, Yanting Li, Renqian Luo, Pipi Hu, Zeru Zhao, Lingbo Li, Guoqing Liu, Zun Wang, Ran Bi, Kaiyuan Gao, Liya Guo, Yu Xie, Chang Liu, Jia Zhang, Tian Xie, Robert Pinsler, Claudio Zeni, Ziheng Lu, Yingce Xia, Marwin H. S. Segler, Maik Riechert, Li Yuan, Lei Chen, Haiguang Liu, Tao Qin
2024	J	`jnl`	Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases. CoRR Krzysztof Maziarz, Guoqing Liu, Hubert Misztela, Aleksei Kornev, Piotr Gainski, Holger Hoefling, Mike Fortunato, Rishi Gupta, Marwin H. S. Segler
2024	J	`jnl`	Generative Active Learning for the Search of Small-molecule Protein Binders. CoRR Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot, Eric Jolicoeur, Edward Ruediger, Andrei Cristian Nica, Emmanuel Bengio, Kostiantyn Lapchevskyi, Daniel St-Cyr, Doris Alexandra Schuetz, Victor Ion Butoi, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio
2024	A*	`conf`	Retro-fallback: retrosynthetic planning in an uncertain world. ICLR Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin H. S. Segler, José Miguel Hernández-Lobato
2024	A*	`conf`	RetroBridge: Modeling Retrosynthesis with Markov Bridges. ICLR Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Michael M. Bronstein, Bruno E. Correia
2024	J	`jnl`	RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNets. CoRR Piotr Gainski, Michal Koziarski, Krzysztof Maziarz, Marwin H. S. Segler, Jacek Tabor, Marek Smieja
2023	J	`jnl`	Are VAEs Bad at Reconstructing Molecular Graphs? CoRR Hagen Münkler, Hubert Misztela, Michal Pikusa, Marwin H. S. Segler, Nadine Schneider, Krzysztof Maziarz
2023	J	`jnl`	PREFER: A New Predictive Modeling Framework for Molecular Discovery. J. Chem. Inf. Model. Jessica Lanini, Gianluca Santarossa, Finton Sirockin, Richard A. Lewis, Nikolas Fechner, Hubert Misztela, Sarah Lewis, Krzysztof Maziarz, Megan Stanley, Marwin H. S. Segler, Nikolaus Stiefl, Nadine Schneider
2023	J	`jnl`	Re-evaluating Retrosynthesis Algorithms with Syntheseus. CoRR Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gainski, Philipp Seidl, Marwin H. S. Segler
2023	J	`jnl`	Retro-fallback: retrosynthetic planning in an uncertain world. CoRR Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin H. S. Segler, José Miguel Hernández-Lobato
2023	J	`jnl`	RetroBridge: Modeling Retrosynthesis with Markov Bridges. CoRR Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Michael M. Bronstein, Bruno E. Correia
2023	A*	`conf`	Retrosynthetic Planning with Dual Value Networks. ICML Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin H. S. Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu
2023	J	`jnl`	Retrosynthetic Planning with Dual Value Networks. CoRR Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin H. S. Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu
2022	J	`jnl`	Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks. J. Chem. Inf. Model. Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Marwin H. S. Segler, Sepp Hochreiter, Günter Klambauer
2022	A*	`conf`	Learning to Extend Molecular Scaffolds with Structural Motifs. ICLR Krzysztof Maziarz, Henry Richard Jackson-Flux, Pashmina Cameron, Finton Sirockin, Nadine Schneider, Nikolaus Stiefl, Marwin H. S. Segler, Marc Brockschmidt
2022	J	`jnl`	RetroGNN: Fast Estimation of Synthesizability for Virtual Screening and De Novo Design by Learning from Slow Retrosynthesis Software. J. Chem. Inf. Model. Cheng-Hao Liu, Maksym Korablyov, Stanislaw Jastrzebski, Pawel Wlodarczyk-Pruszynski, Yoshua Bengio, Marwin H. S. Segler
2021	—	`conf`	FS-Mol: A Few-Shot Learning Dataset of Molecules. NeurIPS Datasets and Benchmarks Megan Stanley, John Bronskill, Krzysztof Maziarz, Hubert Misztela, Jessica Lanini, Marwin H. S. Segler, Nadine Schneider, Marc Brockschmidt
2020	A*	`conf`	Barking up the right tree: an approach to search over molecule synthesis DAGs. NeurIPS John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato
2020	J	`jnl`	Barking up the right tree: an approach to search over molecule synthesis DAGs. CoRR John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato
2020	J	`jnl`	Molecular representation learning with language models and domain-relevant auxiliary tasks. CoRR Benedek Fabian, Thomas Edlich, Héléna Gaspar, Marwin H. S. Segler, Joshua Meyers, Marco Fiscato, Mohamed Ahmed
2020	J	`jnl`	RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design. CoRR Cheng-Hao Liu, Maksym Korablyov, Stanislaw Jastrzebski, Pawel Wlodarczyk-Pruszynski, Yoshua Bengio, Marwin H. S. Segler
2019	—	`conf`	A Generative Model For Electron Paths. ICLR (Poster) John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato
2019	A*	`conf`	A Model to Search for Synthesizable Molecules. NeurIPS John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato
2019	J	`jnl`	A Model to Search for Synthesizable Molecules. CoRR John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato
2019	—	`conf`	Generating Molecules via Chemical Reactions. DGS@ICLR John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato
2019	J	`jnl`	GuacaMol: Benchmarking Models for de Novo Molecular Design. J. Chem. Inf. Model. Nathan Brown, Marco Fiscato, Marwin H. S. Segler, Alain C. Vaucher
2019	J	`jnl`	World Programs for Model-Based Learning and Planning in Compositional State and Action Spaces. CoRR Marwin H. S. Segler
2018	J	`jnl`	DEFactor: Differentiable Edge Factorization-based Probabilistic Graph Generation. CoRR Rim Assouel, Mohamed Ahmed, Marwin H. S. Segler, Amir Saffari, Yoshua Bengio
2018	—	`conf`	Exploring Deep Recurrent Models with Reinforcement Learning for Molecule Design. ICLR (Workshop) Daniel Neil, Marwin H. S. Segler, Laura Guasch, Mohamed Ahmed, Dean Plumbley, Matthew Sellwood, Nathan Brown
2018	J	`jnl`	GuacaMol: Benchmarking Models for De Novo Molecular Design. CoRR Nathan Brown, Marco Fiscato, Marwin H. S. Segler, Alain C. Vaucher
2018	J	`jnl`	Planning chemical syntheses with deep neural networks and symbolic AI. Nat. Marwin H. S. Segler, Mike Preuss, Mark P. Waller
2018	J	`jnl`	Predicting Electron Paths. CoRR John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato
2017	J	`jnl`	Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks. CoRR Marwin H. S. Segler, Thierry Kogej, Christian Tyrchan, Mark P. Waller
2017	J	`jnl`	Learning to Plan Chemical Syntheses. CoRR Marwin H. S. Segler, Mike Preuss, Mark P. Waller
2017	—	`conf`	Towards "AlphaChem": Chemical Synthesis Planning with Tree Search and Deep Neural Network Policies. ICLR (Workshop) Marwin H. S. Segler, Mike Preuss, Mark P. Waller
2017	J	`jnl`	Towards "AlphaChem": Chemical Synthesis Planning with Tree Search and Deep Neural Network Policies. CoRR Marwin H. S. Segler, Mike Preuß, Mark P. Waller
2016	J	`jnl`	Modelling Chemical Reasoning to Predict Reactions. CoRR Marwin H. S. Segler, Mark P. Waller