Search Results - Tripp, Austin

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  1. 1
    DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design

    DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design by García-Ortegón, Miguel, Simm, Gregor N. C., Tripp, Austin J., Hernández-Lobato, José Miguel, Bender, Andreas, Bacallado, Sergio

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  2. 2
    Vibrational Raman Shifts of Spin Isomer Combinations of Hydrogen Dimers and Isotopologues

    Vibrational Raman Shifts of Spin Isomer Combinations of Hydrogen Dimers and Isotopologues by Marr, Adam, Halverson, Thomas, Tripp, Austin, Roy, Pierre-Nicholas

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  3. 3
    Re-evaluating retrosynthesis algorithms with Syntheseus

    Re-evaluating retrosynthesis algorithms with Syntheseus by Maziarz, Krzysztof, Tripp, Austin, Liu, Guoqing, Stanley, Megan, Xie, Shufang, Gaiński, Piotr, Seidl, Philipp, Segler, Marwin H S

    Published in Faraday discussions
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  4. 4
    Petroleomic analysis of the treatment of naphthenic organics in oil sands process-affected water with buoyant photocatalysts

    Petroleomic analysis of the treatment of naphthenic organics in oil sands process-affected water with buoyant photocatalysts by Leshuk, Tim, Peru, Kerry M., de Oliveira Livera, Diogo, Tripp, Austin, Bardo, Patrick, Headley, John V., Gu, Frank

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  5. 5
    Nonequilibrium sensing of volatile compounds using active and passive analyte delivery

    Nonequilibrium sensing of volatile compounds using active and passive analyte delivery by Brandt, Soeren, Pavlichenko, Ida, Shneidman, Anna V, Patel, Haritosh, Tripp, Austin, Wong, Timothy S B, Lazaro, Sean, Thompson, Ethan, Maltz, Aubrey, Storwick, Thomas, Beggs, Holden, Szendrei-Temesi, Katalin, Lotsch, Bettina V, Kaplan, C Nadir, Visser, Claas W, Brenner, Michael P, Murthy, Venkatesh N, Aizenberg, Joanna

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  6. 6
    Diagnosing and fixing common problems in Bayesian optimization for molecule design

    Diagnosing and fixing common problems in Bayesian optimization for molecule design by Tripp, Austin, José Miguel Hernández-Lobato

    Published in arXiv.org
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  7. 7
    Genetic algorithms are strong baselines for molecule generation

    Genetic algorithms are strong baselines for molecule generation by Tripp, Austin, José Miguel Hernández-Lobato

    Published in arXiv.org
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  8. 8
    Tanimoto Random Features for Scalable Molecular Machine Learning

    Tanimoto Random Features for Scalable Molecular Machine Learning by Tripp, Austin, Bacallado, Sergio, Singh, Sukriti, José Miguel Hernández-Lobato

    Published in arXiv.org
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  9. 9
    Generative Model for Synthesizing Ionizable Lipids: A Monte Carlo Tree Search Approach

    Generative Model for Synthesizing Ionizable Lipids: A Monte Carlo Tree Search Approach by Zhao, Jingyi, Ou, Yuxuan, Tripp, Austin, Rasoulianboroujeni, Morteza, José Miguel Hernández-Lobato

    Published in arXiv.org
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  10. 10
    A Deep Generative Model for the Design of Synthesizable Ionizable Lipids

    A Deep Generative Model for the Design of Synthesizable Ionizable Lipids by Ou, Yuxuan, Zhao, Jingyi, Tripp, Austin, Rasoulianboroujeni, Morteza, José Miguel Hernández-Lobato

    Published in arXiv.org
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  11. 11
    Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction

    Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction by Chen, Wenlin, Tripp, Austin, José Miguel Hernández-Lobato

    Published in arXiv.org
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  12. 12
    Batched Bayesian optimization with correlated candidate uncertainties

    Batched Bayesian optimization with correlated candidate uncertainties by Fromer, Jenna, Wang, Runzhong, Manjrekar, Mrunali, Tripp, Austin, José Miguel Hernández-Lobato, Coley, Connor W

    Published in arXiv.org
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  13. 13
    Retro-fallback: retrosynthetic planning in an uncertain world

    Retro-fallback: retrosynthetic planning in an uncertain world by Tripp, Austin, Maziarz, Krzysztof, Lewis, Sarah, Segler, Marwin, José Miguel Hernández-Lobato

    Published in arXiv.org
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  14. 14
    Re-evaluating Retrosynthesis Algorithms with Syntheseus

    Re-evaluating Retrosynthesis Algorithms with Syntheseus by Maziarz, Krzysztof, Tripp, Austin, Liu, Guoqing, Stanley, Megan, Xie, Shufang, Gaiński, Piotr, Seidl, Philipp, Segler, Marwin

    Published in arXiv.org
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  15. 15
    Stochastic Gradient Descent for Gaussian Processes Done Right

    Stochastic Gradient Descent for Gaussian Processes Done Right by Jihao Andreas Lin, Padhy, Shreyas, Antorán, Javier, Tripp, Austin, Terenin, Alexander, Szepesvári, Csaba, José Miguel Hernández-Lobato, Janz, David

    Published in arXiv.org
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  16. 16
    Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining

    Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining by Tripp, Austin, Daxberger, Erik, José Miguel Hernández-Lobato

    Published in arXiv.org
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  17. 17
    Retrosynthetic Planning with Dual Value Networks

    Retrosynthetic Planning with Dual Value Networks by Liu, Guoqing, Xue, Di, Xie, Shufang, Xia, Yingce, Tripp, Austin, Maziarz, Krzysztof, Segler, Marwin, Qin, Tao, Zhang, Zongzhang, Tie-Yan, Liu

    Published in arXiv.org
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  18. 18
    DOCKSTRING: easy molecular docking yields better benchmarks for ligand design

    DOCKSTRING: easy molecular docking yields better benchmarks for ligand design by García-Ortegón, Miguel, Simm, Gregor N C, Tripp, Austin J, José Miguel Hernández-Lobato, Bender, Andreas, Bacallado, Sergio

    Published in arXiv.org
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  19. 19
    GAUCHE: A Library for Gaussian Processes in Chemistry

    GAUCHE: A Library for Gaussian Processes in Chemistry by Ryan-Rhys Griffiths, Klarner, Leo, Moss, Henry B, Ravuri, Aditya, Truong, Sang, Stanton, Samuel, Tom, Gary, Rankovic, Bojana, Du, Yuanqi, Jamasb, Arian, Deshwal, Aryan, Schwartz, Julius, Tripp, Austin, Kell, Gregory, Frieder, Simon, Bourached, Anthony, Chan, Alex, Moss, Jacob, Guo, Chengzhi, Durholt, Johannes, Chaurasia, Saudamini, Strieth-Kalthoff, Felix, Lee, Alpha A, Cheng, Bingqing, Aspuru-Guzik, Alán, Schwaller, Philippe, Tang, Jian

    Published in arXiv.org
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  20. 20
    NIRS-derived skeletal muscle oxidative capacity is correlated with aerobic fitness and independent of sex

    NIRS-derived skeletal muscle oxidative capacity is correlated with aerobic fitness and independent of sex by Beever, Austin T, Tripp, Thomas R, Zhang, Jenny, MacInnis, Martin J

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