Learning from the Harvard Clean Energy Project: The Use of Neural Networks to Accelerate Materials Discovery von Pyzer-Knapp, Edward O., Li, Kewei, Aspuru-Guzik, Alan

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Bayesian Self‐Optimization for Telescoped Continuous Flow Synthesis von Clayton, Adam D., Pyzer‐Knapp, Edward O., Purdie, Mark, Jones, Martin F., Barthelme, Alexandre, Pavey, John, Kapur, Nikil, Chamberlain, Thomas W., Blacker, A. John, Bourne, Richard A.

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What Is High-Throughput Virtual Screening? A Perspective from Organic Materials Discovery von Pyzer-Knapp, Edward O, Suh, Changwon, Gómez-Bombarelli, Rafael, Aguilera-Iparraguirre, Jorge, Aspuru-Guzik, Alán

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Pore-forming activity of clostridial binary toxins von Knapp, O., Benz, R., Popoff, M.R.

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Accelerating materials discovery using artificial intelligence, high performance computing and robotics von Pyzer-Knapp, Edward O., Pitera, Jed W., Staar, Peter W. J., Takeda, Seiji, Laino, Teodoro, Sanders, Daniel P., Sexton, James, Smith, John R., Curioni, Alessandro

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Combining explainable machine learning, demographic and multi-omic data to inform precision medicine strategies for inflammatory bowel disease von Gardiner, Laura-Jayne, Carrieri, Anna Paola, Bingham, Karen, Macluskie, Graeme, Bunton, David, McNeil, Marian, Pyzer-Knapp, Edward O

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Adversarially Learned Anomaly Detection on CMS open data: re-discovering the top quark von Knapp, O., Cerri, O., Dissertori, G., Nguyen, T. Q., Pierini, M., Vlimant, J. R.

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Explainable AI reveals changes in skin microbiome composition linked to phenotypic differences von Carrieri, Anna Paola, Haiminen, Niina, Maudsley-Barton, Sean, Gardiner, Laura-Jayne, Murphy, Barry, Mayes, Andrew E., Paterson, Sarah, Grimshaw, Sally, Winn, Martyn, Shand, Cameron, Hadjidoukas, Panagiotis, Rowe, Will P. M., Hawkins, Stacy, MacGuire-Flanagan, Ashley, Tazzioli, Jane, Kenny, John G., Parida, Laxmi, Hoptroff, Michael, Pyzer-Knapp, Edward O.

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A multi-fidelity machine learning approach to high throughput materials screening von Fare, Clyde, Fenner, Peter, Benatan, Matthew, Varsi, Alessandro, Pyzer-Knapp, Edward O.

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The importance of drought-pathogen interactions in driving oak mortality events in the Ozark Border Region von Wood, Jeffrey D, Knapp, Benjamin O, Muzika, Rose-Marie, Stambaugh, Michael C, Gu, Lianhong

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Controlling the Crystallization of Porous Organic Cages: Molecular Analogs of Isoreticular Frameworks Using Shape-Specific Directing Solvents von Hasell, Tom, Culshaw, Jamie L, Chong, Samantha Y, Schmidtmann, Marc, Little, Marc A, Jelfs, Kim E, Pyzer-Knapp, Edward O, Shepherd, Hilary, Adams, Dave J, Day, Graeme M, Cooper, Andrew I

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A Bayesian approach to calibrating high-throughput virtual screening results and application to organic photovoltaic materials von Pyzer-Knapp, Edward O, Simm, Gregor N, Aspuru Guzik, Alán

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Advancing biomolecular simulation through exascale HPC, AI and quantum computing von Pyzer-Knapp, Edward O., Curioni, Alessandro

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Forty-Eight Years of Forest Succession: Tree Species Change across Four Forest Types in Mid-Missouri von Knapp, Benjamin O, Pallardy, Stephen G

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The Harvard organic photovoltaic dataset von Lopez, Steven A., Pyzer-Knapp, Edward O., Simm, Gregor N., Lutzow, Trevor, Li, Kewei, Seress, Laszlo R., Hachmann, Johannes, Aspuru-Guzik, Alán

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Hessian QM9: A quantum chemistry database of molecular Hessians in implicit solvents von Williams, Nicholas J., Kabalan, Lara, Stojanovic, Ljiljana, Zólyomi, Viktor, Pyzer-Knapp, Edward O.

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Predicted crystal energy landscapes of porous organic cages von Pyzer-Knapp, Edward O., Thompson, Hugh P. G., Schiffmann, Florian, Jelfs, Kim E., Chong, Samantha Y., Little, Marc A., Cooper, Andrew I., Day, Graeme M.

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Explainable Gaussian processes: a loss landscape perspective von Niroomand, Maximilian P, Dicks, Luke, Pyzer-Knapp, Edward O, Wales, David J

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Evolving the Materials Genome: How Machine Learning Is Fueling the Next Generation of Materials Discovery von Suh, Changwon, Fare, Clyde, Warren, James A, Pyzer-Knapp, Edward O

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Welcome to the first issue of Applied AI Letters von Pyzer‐Knapp, Edward O., Cuff, James, Patterson, Jack, Isayev, Olexandr, Maskell, Simon

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