Edward O. Pyzer-Knapp

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 16

Top Topics

Machine Learning

Gaussian Process

Virtual Screening

Top Venues

J. Chem. Inf. Model.

IBM J. Res. Dev.

Publications

Maximilian P. Niroomand, Luke Dicks, Edward O. Pyzer-Knapp, David J. Wales
Physics Inspired Approaches Towards Understanding Gaussian Processes. CoRR (2023)
Robert Allison, Anthony Stephenson, Samuel F, Edward O. Pyzer-Knapp
Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression. NeurIPS (2023)
David E. Graff, Matteo Aldeghi, Joseph A. Morrone, Kirk E. Jordan, Edward O. Pyzer-Knapp, Connor W. Coley
Self-focusing virtual screening with active design space pruning. CoRR (2022)
David E. Graff, Matteo Aldeghi, Joseph A. Morrone, Kirk E. Jordan, Edward O. Pyzer-Knapp, Connor W. Coley
Self-Focusing Virtual Screening with Active Design Space Pruning. J. Chem. Inf. Model. 62 (16) (2022)
Matteo Aldeghi, David E. Graff, Nathan C. Frey, Joseph A. Morrone, Edward O. Pyzer-Knapp, Kirk E. Jordan, Connor W. Coley
Roughness of Molecular Property Landscapes and Its Impact on Modellability. J. Chem. Inf. Model. 62 (19) (2022)
Clyde Fare, Peter Fenner, Edward O. Pyzer-Knapp
A Principled Method for the Creation of Synthetic Multi-fidelity Data Sets. CoRR (2022)
Edward O. Pyzer-Knapp
Using Bayesian Optimization to Accelerate Virtual Screening for the Discovery of Therapeutics Appropriate for Repurposing for COVID-19. CoRR (2020)
Peter Fenner, Edward O. Pyzer-Knapp
Privacy-Preserving Gaussian Process Regression - A Modular Approach to the Application of Homomorphic Encryption. CoRR (2020)
James L. McDonagh, Ardita Shkurti, David J. Bray, Richard L. Anderson, Edward O. Pyzer-Knapp
Utilizing Machine Learning for Efficient Parameterization of Coarse Grained Molecular Force Fields. J. Chem. Inf. Model. 59 (10) (2019)
Matt Benatan, Edward O. Pyzer-Knapp
Fully Bayesian Recurrent Neural Networks for Safe Reinforcement Learning. CoRR (2019)
Anna Paola Carrieri, Will P. M. Rowe, Martyn D. Winn, Edward O. Pyzer-Knapp
A Fast Machine Learning Workflow for Rapid Phenotype Prediction from Whole Shotgun Metagenomes. AAAI (2019)
Edward O. Pyzer-Knapp
Bayesian optimization for accelerated drug discovery. IBM J. Res. Dev. 62 (6) (2018)
Clyde Fare, Lukas Turcani, Edward O. Pyzer-Knapp
Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks. CoRR (2018)
Dipti Jasrasaria, Edward O. Pyzer-Knapp
Dynamic Control of Explore/Exploit Trade-Off In Bayesian Optimization. CoRR (2018)
Matthew Groves, Edward O. Pyzer-Knapp
Efficient and Scalable Batch Bayesian Optimization Using K-Means. CoRR (2018)
José Miguel Hernández-Lobato, James Requeima, Edward O. Pyzer-Knapp, Alán Aspuru-Guzik
Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space. ICML (2017)