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Like many scientific fields, new chemistry literature has grown at a staggering pace, with thousands of papers released every month.
Weininger, D.: Smiles, a chemical language and information system. 1. introduction to methodology and encoding rules. J. Chem. Inf. Comput. Sci. 28
1988
Earlier work this paper cites.
Weininger, D., Weininger, A., Weininger, J.: Smiles. 2. algorithm for generation of unique smiles notation. J. Chem. Inf. Comput. Sci. 29
1989
Earlier work this paper cites.
LeCun, Y., Bengio, Y.: Convolutional networks for images, speech, and time series (1998)
1998
Earlier work this paper cites.
Durant, J.L., Leland, B.A., Henry, D., Nourse, J.G.: Reoptimization of mdl keys for use in drug discovery. Journal of chemical information and computer sciences 42 6
2002
Earlier work this paper cites.
Papineni, K., Roukos, S., Ward, T., Zhu, W.J.: Bleu: a method for automatic evaluation of machine translation. In: ACL (2002)
2002
Earlier work this paper cites.
Fukushima, K.: Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biological Cybernetics 36
2004
Earlier work this paper cites.
Lin, C.Y.: Rouge: A package for automatic evaluation of summaries. In: ACL 2004 (2004)
2004
Earlier work this paper cites.
Dunkel, M., Günther, S., Ahmed, J., Wittig, B., Preissner, R.: Superpred: drug classification and target prediction. Nucleic Acids Research 36
2008
Earlier work this paper cites.
Filippov, I.V., Nicklaus, M.: Optical structure recognition software to recover chemical information: Osra, an open source solution. Journal of chemical information and modeling 49 3
2009
Earlier work this paper cites.
Miller, F.P., Vandome, A., McBrewster, J.: Levenshtein distance: Information theory, computer science, string (computer science), string metric, damerau?levenshtein distance, spell checker, hamming distance (2009)
2009
Earlier work this paper cites.
Rogers, D., Hahn, M.: Extended-connectivity fingerprints. Journal of chemical information and modeling 50 5
2010
Earlier work this paper cites.
Park, J., Li, Y., Rosania, G., Saitou, K.: Image-to-structure task by chemreader. In: TREC (2011)
2011
Earlier work this paper cites.
Lowe, D.M.: Extraction of chemical structures and reactions from the literature (2012)
2012
Earlier work this paper cites.
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A.C., Bengio, Y.: Generative adversarial nets. In: NIPS (2014)
2014
Earlier work this paper cites.
Kingma, D.P., Welling, M.: Auto-encoding variational bayes. CoRR abs/1312.6114
2014
Earlier work this paper cites.
Lin, T.Y., Maire, M., Belongie, S.J., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: Microsoft coco: Common objects in context. In: ECCV (2014)
2014
Earlier work this paper cites.
Bajusz, D., Rácz, A., Héberger, K.: Why is tanimoto index an appropriate choice for fingerprint-based similarity calculations? Journal of Cheminformatics 7
2015
Earlier work this paper cites.
Karpathy, A., Fei-Fei, L.: Deep visual-semantic alignments for generating image descriptions. In: CVPR (2015)
2015
Earlier work this paper cites.
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M.S., Berg, A., Fei-Fei, L.: Imagenet large scale visual recognition challenge. International Journal of Computer Vision 115
2015
Cited alongside, same era.
Schneider, N., Sayle, R., Landrum, G.: Get your atoms in order - an open-source implementation of a novel and robust molecular canonicalization algorithm. Journal of chemical information and modeling 55 10
2015
Cited alongside, same era.
2015
Cited alongside, same era.
Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A.C., Salakhutdinov, R., Zemel, R., Bengio, Y.: Show, attend and tell: Neural image caption generation with visual attention. In: ICML (2015)
2015
Cited alongside, same era.
Elton, D., Boukouvalas, Z., Fuge, M., Chung, P.W.: Deep learning for molecular design—a review of the state of the art (2019)
2019
Later among the works it cites.
Krenn, M., Hase, F., Nigam, A., Friederich, P., Aspuru-Guzik, A.: Self-referencing embedded strings (selfies): A 100% robust molecular string representation. arXiv: Learning (2019)
2019
Later among the works it cites.
Liu, K., Sun, X., Jia, L., Ma, J., Xing, H., Wu, J., Gao, H., Sun, Y., Boulnois, F., Fan, J.: Chemi-net: A molecular graph convolutional network for accurate drug property prediction. International Journal of Molecular Sciences 20
2019
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Loshchilov, I., Hutter, F.: Decoupled weight decay regularization. In: ICLR (2019)
2019
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Ramsundar, B., Eastman, P., Walters, P., Pande, V., Leswing, K., Wu, Z.: Deep Learning for the Life Sciences. O’Reilly Media (2019), https://www.amazon.com/Deep-Learning-Life-Sciences-Microscopy/dp/1492039837
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He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp. 770–778 (2016)
2016
Cited alongside, same era.
Kim, S., Thiessen, P., Bolton, E.E., Chen, J., Fu, G., Gindulyte, A., Han, L., He, J., He, S., Shoemaker, B., Wang, J., Yu, B., Zhang, J., Bryant, S.: Pubchem substance and compound databases. Nucleic Acids Research 44
2016
Cited alongside, same era.
2016
Cited alongside, same era.
Tran, K., He, X., Zhang, L., Sun, J.: Rich image captioning in the wild. 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) pp. 434–441 (2016)
2016
Cited alongside, same era.
2016
Cited alongside, same era.
2017
Cited alongside, same era.
Venugopalan, S., Hendricks, L.A., Rohrbach, M., Mooney, R., Darrell, T., Saenko, K.: Captioning images with diverse objects. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp. 1170–1178 (2017)
2017
Cited alongside, same era.
Wu, Z., Ramsundar, B., Feinberg, E., Gomes, J., Geniesse, C., Pappu, A.S., Leswing, K., Pande, V.: Moleculenet: A benchmark for molecular machine learning. arXiv: Learning (2017)
2017
Cited alongside, same era.
2019
Later among the works it cites.
Arús-Pous, J., Patronov, A., Bjerrum, E., Tyrchan, C., Reymond, J., Chen, H., Engkvist, O.: Smiles-based deep generative scaffold decorator for de-novo drug design. Journal of Cheminformatics 12
2020
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Beard, E.J., Cole, J.: Chemschematicresolver: A toolkit to decode 2d chemical diagrams with labels and r-groups into annotated chemical named entities. Journal of chemical information and modeling (2020)
2020
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2020
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2020
Later among the works it cites.
2020
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Nayak, P., Silberfarb, A., Chen, R., Muezzinoglu, T., Byrnes, J.: Transformer based molecule encoding for property prediction. arXiv: Quantitative Methods (2020)
2020
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Oldenhof, M., Arany, A., Moreau, Y., Simm, J.: Chemgrapher: Optical graph recognition of chemical compounds by deep learning. Journal of chemical information and modeling (2020)
2020
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Rajan, K., Brinkhaus, H.O., Zielesny, A., Steinbeck, C.: A review of optical chemical structure recognition tools. Journal of Cheminformatics 12
2020
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Rajan, K., Zielesny, A., Steinbeck, C.: Decimer: towards deep learning for chemical image recognition. Journal of Cheminformatics 12
2020
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Schwaller, P., Vaucher, A., Laino, T., Reymond, J.: Prediction of chemical reaction yields using deep learning (2020)
2020
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RDKit: open-source cheminformatics software. https://rdkit.org/ , accessed: 2021-05-09
2021
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