BibTeX records: Garrett B. Goh

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@article{DBLP:journals/corr/abs-1910-03741,
  author    = {Haoran Wei and
               Mariefel Olarte and
               Garrett B. Goh},
  title     = {Multiple-objective Reinforcement Learning for Inverse Design and Identification},
  journal   = {CoRR},
  volume    = {abs/1910.03741},
  year      = {2019},
  url       = {http://arxiv.org/abs/1910.03741},
  eprinttype = {arXiv},
  eprint    = {1910.03741},
  timestamp = {Wed, 16 Oct 2019 01:00:00 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1910-03741.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{DBLP:journals/corr/abs-1911-06876,
  author    = {Lawrence Phillips and
               Garrett B. Goh and
               Nathan O. Hodas},
  title     = {Explanatory Masks for Neural Network Interpretability},
  journal   = {CoRR},
  volume    = {abs/1911.06876},
  year      = {2019},
  url       = {http://arxiv.org/abs/1911.06876},
  eprinttype = {arXiv},
  eprint    = {1911.06876},
  timestamp = {Mon, 02 Dec 2019 00:00:00 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1911-06876.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{DBLP:conf/bigdataconf/SaklothBPG18,
  author    = {Khushmeen Sakloth and
               Wesley Beckner and
               Jim Pfaendtner and
               Garrett B. Goh},
  editor    = {Naoki Abe and
               Huan Liu and
               Calton Pu and
               Xiaohua Hu and
               Nesreen K. Ahmed and
               Mu Qiao and
               Yang Song and
               Donald Kossmann and
               Bing Liu and
               Kisung Lee and
               Jiliang Tang and
               Jingrui He and
               Jeffrey S. Saltz},
  title     = {IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural
               Networks},
  booktitle = {{IEEE} International Conference on Big Data {(IEEE} BigData 2018),
               Seattle, WA, USA, December 10-13, 2018},
  pages     = {1465--1473},
  publisher = {{IEEE}},
  year      = {2018},
  url       = {https://doi.org/10.1109/BigData.2018.8622512},
  doi       = {10.1109/BigData.2018.8622512},
  timestamp = {Fri, 19 Nov 2021 16:08:20 +0100},
  biburl    = {https://dblp.org/rec/conf/bigdataconf/SaklothBPG18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{DBLP:conf/kdd/GohSVH18,
  author    = {Garrett B. Goh and
               Charles Siegel and
               Abhinav Vishnu and
               Nathan Oken Hodas},
  editor    = {Yike Guo and
               Faisal Farooq},
  title     = {Using Rule-Based Labels for Weak Supervised Learning: {A} ChemNet
               for Transferable Chemical Property Prediction},
  booktitle = {Proceedings of the 24th {ACM} {SIGKDD} International Conference on
               Knowledge Discovery {\&} Data Mining, {KDD} 2018, London, UK,
               August 19-23, 2018},
  pages     = {302--310},
  publisher = {{ACM}},
  year      = {2018},
  url       = {https://doi.org/10.1145/3219819.3219838},
  doi       = {10.1145/3219819.3219838},
  timestamp = {Wed, 21 Nov 2018 12:44:27 +0100},
  biburl    = {https://dblp.org/rec/conf/kdd/GohSVH18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{DBLP:conf/wacv/GohSVHB18,
  author    = {Garrett B. Goh and
               Charles Siegel and
               Abhinav Vishnu and
               Nathan O. Hodas and
               Nathan Baker},
  title     = {How Much Chemistry Does a Deep Neural Network Need to Know to Make
               Accurate Predictions?},
  booktitle = {2018 {IEEE} Winter Conference on Applications of Computer Vision,
               {WACV} 2018, Lake Tahoe, NV, USA, March 12-15, 2018},
  pages     = {1340--1349},
  publisher = {{IEEE} Computer Society},
  year      = {2018},
  url       = {https://doi.org/10.1109/WACV.2018.00151},
  doi       = {10.1109/WACV.2018.00151},
  timestamp = {Wed, 16 Oct 2019 14:14:49 +0200},
  biburl    = {https://dblp.org/rec/conf/wacv/GohSVHB18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{DBLP:journals/corr/abs-1808-04456,
  author    = {Garrett B. Goh and
               Khushmeen Sakloth and
               Charles Siegel and
               Abhinav Vishnu and
               Jim Pfaendtner},
  title     = {Multimodal Deep Neural Networks using Both Engineered and Learned
               Representations for Biodegradability Prediction},
  journal   = {CoRR},
  volume    = {abs/1808.04456},
  year      = {2018},
  url       = {http://arxiv.org/abs/1808.04456},
  eprinttype = {arXiv},
  eprint    = {1808.04456},
  timestamp = {Sun, 27 Jan 2019 00:00:00 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1808-04456.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{DBLP:journals/corr/abs-1809-05127,
  author    = {Khushmeen Sakloth and
               Wesley Beckner and
               Jim Pfaendtner and
               Garrett B. Goh},
  title     = {IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural
               Networks},
  journal   = {CoRR},
  volume    = {abs/1809.05127},
  year      = {2018},
  url       = {http://arxiv.org/abs/1809.05127},
  eprinttype = {arXiv},
  eprint    = {1809.05127},
  timestamp = {Sun, 27 Jan 2019 00:00:00 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1809-05127.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{DBLP:journals/jcc/GohHV17,
  author    = {Garrett B. Goh and
               Nathan O. Hodas and
               Abhinav Vishnu},
  title     = {Deep learning for computational chemistry},
  journal   = {J. Comput. Chem.},
  volume    = {38},
  number    = {16},
  pages     = {1291--1307},
  year      = {2017},
  url       = {https://doi.org/10.1002/jcc.24764},
  doi       = {10.1002/jcc.24764},
  timestamp = {Wed, 01 Apr 2020 01:00:00 +0200},
  biburl    = {https://dblp.org/rec/journals/jcc/GohHV17.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{DBLP:journals/corr/abs-1701-04503,
  author    = {Garrett B. Goh and
               Nathan O. Hodas and
               Abhinav Vishnu},
  title     = {Deep Learning for Computational Chemistry},
  journal   = {CoRR},
  volume    = {abs/1701.04503},
  year      = {2017},
  url       = {http://arxiv.org/abs/1701.04503},
  eprinttype = {arXiv},
  eprint    = {1701.04503},
  timestamp = {Tue, 09 Oct 2018 01:00:00 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1701-04503.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{DBLP:journals/corr/GohSVHB17,
  author    = {Garrett B. Goh and
               Charles Siegel and
               Abhinav Vishnu and
               Nathan Oken Hodas and
               Nathan Baker},
  title     = {Chemception: {A} Deep Neural Network with Minimal Chemistry Knowledge
               Matches the Performance of Expert-developed {QSAR/QSPR} Models},
  journal   = {CoRR},
  volume    = {abs/1706.06689},
  year      = {2017},
  url       = {http://arxiv.org/abs/1706.06689},
  eprinttype = {arXiv},
  eprint    = {1706.06689},
  timestamp = {Mon, 13 Aug 2018 01:00:00 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/GohSVHB17.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{DBLP:journals/corr/abs-1710-02238,
  author    = {Garrett B. Goh and
               Charles Siegel and
               Abhinav Vishnu and
               Nathan O. Hodas and
               Nathan Baker},
  title     = {How Much Chemistry Does a Deep Neural Network Need to Know to Make
               Accurate Predictions?},
  journal   = {CoRR},
  volume    = {abs/1710.02238},
  year      = {2017},
  url       = {http://arxiv.org/abs/1710.02238},
  eprinttype = {arXiv},
  eprint    = {1710.02238},
  timestamp = {Mon, 13 Aug 2018 01:00:00 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1710-02238.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{DBLP:journals/corr/abs-1712-02034,
  author    = {Garrett B. Goh and
               Nathan O. Hodas and
               Charles Siegel and
               Abhinav Vishnu},
  title     = {SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for
               Predicting Chemical Properties},
  journal   = {CoRR},
  volume    = {abs/1712.02034},
  year      = {2017},
  url       = {http://arxiv.org/abs/1712.02034},
  eprinttype = {arXiv},
  eprint    = {1712.02034},
  timestamp = {Mon, 13 Aug 2018 01:00:00 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1712-02034.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{DBLP:journals/corr/abs-1712-02734,
  author    = {Garrett B. Goh and
               Charles Siegel and
               Abhinav Vishnu and
               Nathan O. Hodas},
  title     = {ChemNet: {A} Transferable and Generalizable Deep Neural Network for
               Small-Molecule Property Prediction},
  journal   = {CoRR},
  volume    = {abs/1712.02734},
  year      = {2017},
  url       = {http://arxiv.org/abs/1712.02734},
  eprinttype = {arXiv},
  eprint    = {1712.02734},
  timestamp = {Mon, 13 Aug 2018 01:00:00 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1712-02734.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{DBLP:journals/jcisd/LexaGC14,
  author    = {Katrina W. Lexa and
               Garrett B. Goh and
               Heather A. Carlson},
  title     = {Parameter Choice Matters: Validating Probe Parameters for Use in Mixed-Solvent
               Simulations},
  journal   = {J. Chem. Inf. Model.},
  volume    = {54},
  number    = {8},
  pages     = {2190--2199},
  year      = {2014},
  url       = {https://doi.org/10.1021/ci400741u},
  doi       = {10.1021/ci400741u},
  timestamp = {Fri, 06 Mar 2020 00:00:00 +0100},
  biburl    = {https://dblp.org/rec/journals/jcisd/LexaGC14.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
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