1 code implementation • 30 Oct 2023 • Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gaiński, Philipp Seidl, Marwin Segler
The planning of how to synthesize molecules, also known as retrosynthesis, has been a growing focus of the machine learning and chemistry communities in recent years.
1 code implementation • 13 Oct 2023 • Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin Segler, José Miguel Hernández-Lobato
Retrosynthesis is the task of planning a series of chemical reactions to create a desired molecule from simpler, buyable molecules.
no code implementations • 4 May 2023 • Hagen Muenkler, Hubert Misztela, Michal Pikusa, Marwin Segler, Nadine Schneider, Krzysztof Maziarz
Many contemporary generative models of molecules are variational auto-encoders of molecular graphs.
1 code implementation • 31 Jan 2023 • Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu
Retrosynthesis, which aims to find a route to synthesize a target molecule from commercially available starting materials, is a critical task in drug discovery and materials design.
Ranked #1 on Multi-step retrosynthesis on USPTO-190
no code implementations • 28 Apr 2021 • Krzysztof Maziarz, Anna Krason, Zbigniew Wojna
Recent advancements in computer vision promise to automate medical image analysis.
3 code implementations • ICLR 2022 • Krzysztof Maziarz, Henry Jackson-Flux, Pashmina Cameron, Finton Sirockin, Nadine Schneider, Nikolaus Stiefl, Marwin Segler, Marc Brockschmidt
Recent advancements in deep learning-based modeling of molecules promise to accelerate in silico drug discovery.
no code implementations • 23 Aug 2020 • Zbigniew Wojna, Krzysztof Maziarz, Łukasz Jocz, Robert Pałuba, Robert Kozikowski, Iasonas Kokkinos
To this end, we introduce a new benchmarking dataset, consisting of 49426 images (top-view and street-view) of 9674 buildings.
no code implementations • 10 Oct 2019 • Krzysztof Maziarz, Efi Kokiopoulou, Andrea Gesmundo, Luciano Sbaiz, Gabor Bartok, Jesse Berent
The binary allocation variables are learned jointly with the model parameters by standard back-propagation thanks to the Gumbel-Softmax reparametrization method.
Ranked #1 on Multi-Task Learning on OMNIGLOT
no code implementations • 25 Sep 2019 • Krzysztof Maziarz, Mingxing Tan, Andrey Khorlin, Kuang-Yu Samuel Chang, Andrea Gesmundo
We show that the Evo-NAS agent outperforms both neural and evolutionary agents when applied to architecture search for a suite of text and image classification benchmarks.
no code implementations • 25 Sep 2019 • Krzysztof Maziarz, Efi Kokiopoulou, Andrea Gesmundo, Luciano Sbaiz, Gabor Bartok, Jesse Berent
We propose the Gumbel-Matrix routing, a novel multi-task routing method based on the Gumbel-Softmax, that is designed to learn fine-grained parameter sharing.
no code implementations • 24 Nov 2018 • Krzysztof Maziarz, Mingxing Tan, Andrey Khorlin, Marin Georgiev, Andrea Gesmundo
We show that the Evo-NAS agent outperforms both neural and evolutionary agents when applied to architecture search for a suite of text and image classification benchmarks.
4 code implementations • 23 Jan 2017 • Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, Jeff Dean
In this work, we address these challenges and finally realize the promise of conditional computation, achieving greater than 1000x improvements in model capacity with only minor losses in computational efficiency on modern GPU clusters.
Ranked #14 on Language Modelling on One Billion Word