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Retrosynthesis is one of the fundamental problems in organic chemistry.
Computer-assisted design of complex organic syntheses
EJ Corey and W Todd Wipke · 1969
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The logic of chemical synthesis: multistep synthesis of complex carbogenic molecules (nobel lecture)
Elias JAMES Corey · 1991
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Markov logic networks
Matthew Richardson and Pedro Domingos · 2006
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The graph neural network model
Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini · 2008
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Elements of information theory
Thomas M Cover and Joy A Thomas · 2012
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P Adams · 2015
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Gated graph sequence neural networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard Zemel · 2015
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Discriminative embeddings of latent variable models for structured data
Hanjun Dai, Bo Dai, and Le Song · 2016
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Quantization based fast inner product search
Ruiqi Guo, Sanjiv Kumar, Krzysztof Choromanski, and David Simcha · 2016
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Predicting organic reaction outcomes with weisfeiler-lehman network
Wengong Jin, Connor Coley, Regina Barzilay, and Tommi Jaakkola · 2017
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Computer-assisted retrosynthesis based on molecular similarity
Connor W Coley, Luke Rogers, William H Green, and Klavs F Jensen · 2017
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Retrosynthetic reaction prediction using neural sequence-to-sequence models
Deep sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan R Salakhutdinov, and Alexander J Smola · 2017
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Neural message passing for quantum chemistry
Justin Gilmer, Samuel S Schoenholz, Patrick F Riley, Oriol Vinyals, and George E Dahl · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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A generative model for electron paths
John Bradshaw, Matt J Kusner, Brooks Paige, Marwin HS Segler, and José Miguel Hernández-Lobato · 2018
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“found in translation”: predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models
Philippe Schwaller, Theophile Gaudin, David Lanyi, Costas Bekas, and Teodoro Laino · 2018
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Planning chemical syntheses with deep neural networks and symbolic ai
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Bowen Liu, Bharath Ramsundar, Prasad Kawthekar, Jade Shi, Joseph Gomes, Quang Luu Nguyen, Stephen Ho, Jack Sloane, Paul Wender, and Vijay Pande · 2017
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Deriving neural architectures from sequence and graph kernels
Tao Lei, Wengong Jin, Regina Barzilay, and Tommi Jaakkola · 2017
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Inductive representation learning on large graphs
Will Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio · 2017
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Machine learning in computer-aided synthesis planning
Connor W. Coley, William H. Green, and Klavs F. Jensen
Cited in the paper.
A graph-convolutional neural network model for the prediction of chemical reactivity
Connor W. Coley, Wengong Jin, Luke Rogers, Timothy F. Jamison, Tommi S. Jaakkola, William H. Green, Regina Barzilay, and Klavs F. Jensen
Cited in the paper.
Computer-assisted synthetic planning: The end of the beginning
Sara Szymkuc, Ewa P. Gajewska, Tomasz Klucznik, Karol Molga, Piotr Dittwald, Michał Startek, Michał Bajczyk, and Bartosz A. Grzybowski
Cited in the paper.
Marwin HS Segler, Mike Preuss, and Mark P Waller · 2018
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How powerful are graph neural networks?
Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka · 2018
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A transformer model for retrosynthesis
Pavel Karpov, Guillaume Godin, and I Tetko · 2019
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Learning retrosynthetic planning through self-play
John S Schreck, Connor W Coley, and Kyle JM Bishop · 2019
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