Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. - Noam Shazeer; Azalia Mirhoseini; Krzysztof Maziarz; Andy Davis; Quoc V. Le; Geoffrey E. Hinton; Jeff Dean (ICLR (Poster), 2017)

Evolutionary-Neural Hybrid Agents for Architecture Search. - Krzysztof Maziarz; Andrey Khorlin; Quentin de Laroussilhe; Andrea Gesmundo (CoRR, 2018)

Gumbel-Matrix Routing for Flexible Multi-task Learning. - Krzysztof Maziarz; Efi Kokiopoulou; Andrea Gesmundo; Luciano Sbaiz; Gábor Bartók; Jesse Berent (CoRR, 2019)

Holistic Multi-View Building Analysis in the Wild with Projection Pooling. - Zbigniew Wojna; Krzysztof Maziarz; Lukasz Jocz; Robert Paluba; Robert Kozikowski; Iasonas Kokkinos (AAAI, 2021)

FS-Mol: A Few-Shot Learning Dataset of Molecules. - Megan Stanley; John Bronskill; Krzysztof Maziarz; Hubert Misztela; Jessica Lanini; Marwin H. S. Segler; Nadine Schneider; Marc Brockschmidt (NeurIPS Datasets and Benchmarks, 2021)

Hashing modulo alpha-equivalence. - Krzysztof Maziarz; Tom Ellis; Alan Lawrence; Andrew W. Fitzgibbon; Simon Peyton Jones (PLDI, 2021)

Learning to Extend Molecular Scaffolds with Structural Motifs. - Krzysztof Maziarz; Henry Jackson-Flux; Pashmina Cameron; Finton Sirockin; Nadine Schneider; Nikolaus Stiefl; Marc Brockschmidt (CoRR, 2021)

Deep Learning for Rheumatoid Arthritis: Joint Detection and Damage Scoring in X-rays. - Krzysztof Maziarz; Anna Krason; Zbigniew Wojna (CoRR, 2021)

Learning to Extend Molecular Scaffolds with Structural Motifs. - Krzysztof Maziarz; Henry Richard Jackson-Flux; Pashmina Cameron; Finton Sirockin; Nadine Schneider; Nikolaus Stiefl; Marwin H. S. Segler; Marc Brockschmidt (ICLR, 2022)

Retrosynthetic Planning with Dual Value Networks. - Guoqing Liu; Di Xue; Shufang Xie 003; Yingce Xia; Austin Tripp; Krzysztof Maziarz; Marwin H. S. Segler; Tao Qin 001; Zongzhang Zhang; Tie-Yan Liu (ICML, 2023)

Are VAEs Bad at Reconstructing Molecular Graphs? - Hagen Münkler; Hubert Misztela; Michal Pikusa; Marwin H. S. Segler; Nadine Schneider; Krzysztof Maziarz (CoRR, 2023)

Re-evaluating Retrosynthesis Algorithms with Syntheseus. - Krzysztof Maziarz; Austin Tripp; Guoqing Liu; Megan Stanley; Shufang Xie 003; Piotr Gainski; Philipp Seidl; Marwin H. S. Segler (CoRR, 2023)

PREFER: A New Predictive Modeling Framework for Molecular Discovery. - 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 (J. Chem. Inf. Model., 2023)

Retro-fallback: retrosynthetic planning in an uncertain world. - Austin Tripp; Krzysztof Maziarz; Sarah Lewis; Marwin H. S. Segler; José Miguel Hernández-Lobato (ICLR, 2024)

RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNets. - Piotr Gainski; Michal Koziarski; Krzysztof Maziarz; Marwin H. S. Segler; Jacek Tabor; Marek Smieja (CoRR, 2024)

Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases. - Krzysztof Maziarz; Guoqing Liu; Hubert Misztela; Aleksei Kornev; Piotr Gainski; Holger Hoefling; Mike Fortunato; Rishi Gupta; Marwin H. S. Segler (CoRR, 2024)

Diverse and feasible retrosynthesis using GFlowNets. - Piotr Gainski; Michal Koziarski; Krzysztof Maziarz; Marwin H. S. Segler; Jacek Tabor; Marek Smieja (Inf. Sci., 2025)

NatureLM: Deciphering the Language of Nature for Scientific Discovery. - Yingce Xia; Peiran Jin; Shufang Xie 003; Liang He 010; Chuan Cao; Renqian Luo; Guoqing Liu; Yue Wang 017; Zequn Liu; Yuan-Jyue Chen; Zekun Guo; Yeqi Bai; et al. (CoRR, 2025)