Edward O. Pyzer-Knapp

20 papers A* 3Journal 17
YearRankTypeTitle / Venue / Authors
2025 J jnl
Refining embeddings with fill-tuning: data-efficient generalised performance improvements for materials foundation models.
CoRR
Matthew P. Wilson, Edward O. Pyzer-Knapp, Nicolas Galichet, Luke Dicks
2024 J jnl
Explainable Gaussian processes: a loss landscape perspective.
Mach. Learn. Sci. Technol.
Maximilian P. Niroomand, Luke Dicks, Edward O. Pyzer-Knapp, David J. Wales
2024 J jnl
Hessian QM9: A quantum chemistry database of molecular Hessians in implicit solvents.
CoRR
Nicholas J. Williams, Lara Kabalan, Ljiljana Stojanovic, Viktor Zolyomi, Edward O. Pyzer-Knapp
2024 J jnl
TopSearch: a Python package for topographical analysis of machine learning models and physical systems.
J. Open Source Softw.
Luke Dicks, Edward O. Pyzer-Knapp
2023 A* conf
Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression.
NeurIPS
Robert Allison, Anthony Stephenson, Samuel F, Edward O. Pyzer-Knapp
2023 J jnl
Physics Inspired Approaches Towards Understanding Gaussian Processes.
CoRR
Maximilian P. Niroomand, Luke Dicks, Edward O. Pyzer-Knapp, David J. Wales
2022 J jnl
A Principled Method for the Creation of Synthetic Multi-fidelity Data Sets.
CoRR
Clyde Fare, Peter Fenner, Edward O. Pyzer-Knapp
2022 J jnl
Roughness of Molecular Property Landscapes and Its Impact on Modellability.
J. Chem. Inf. Model.
Matteo Aldeghi, David E. Graff, Nathan C. Frey, Joseph A. Morrone, Edward O. Pyzer-Knapp, Kirk E. Jordan, Connor W. Coley
2022 J jnl
Self-Focusing Virtual Screening with Active Design Space Pruning.
J. Chem. Inf. Model.
David E. Graff, Matteo Aldeghi, Joseph A. Morrone, Kirk E. Jordan, Edward O. Pyzer-Knapp, Connor W. Coley
2022 J jnl
Self-focusing virtual screening with active design space pruning.
CoRR
David E. Graff, Matteo Aldeghi, Joseph A. Morrone, Kirk E. Jordan, Edward O. Pyzer-Knapp, Connor W. Coley
2020 J jnl
Privacy-Preserving Gaussian Process Regression - A Modular Approach to the Application of Homomorphic Encryption.
CoRR
Peter Fenner, Edward O. Pyzer-Knapp
2020 J jnl
Using Bayesian Optimization to Accelerate Virtual Screening for the Discovery of Therapeutics Appropriate for Repurposing for COVID-19.
CoRR
Edward O. Pyzer-Knapp
2019 A* conf
A Fast Machine Learning Workflow for Rapid Phenotype Prediction from Whole Shotgun Metagenomes.
AAAI
Anna Paola Carrieri, Will P. M. Rowe, Martyn D. Winn, Edward O. Pyzer-Knapp
2019 J jnl
Fully Bayesian Recurrent Neural Networks for Safe Reinforcement Learning.
CoRR
Matt Benatan, Edward O. Pyzer-Knapp
2019 J jnl
Utilizing Machine Learning for Efficient Parameterization of Coarse Grained Molecular Force Fields.
J. Chem. Inf. Model.
James L. McDonagh, Ardita Shkurti, David J. Bray, Richard L. Anderson, Edward O. Pyzer-Knapp
2018 J jnl
Bayesian optimization for accelerated drug discovery.
IBM J. Res. Dev.
Edward O. Pyzer-Knapp
2018 J jnl
Dynamic Control of Explore/Exploit Trade-Off In Bayesian Optimization.
CoRR
Dipti Jasrasaria, Edward O. Pyzer-Knapp
2018 J jnl
Efficient and Scalable Batch Bayesian Optimization Using K-Means.
CoRR
Matthew Groves, Edward O. Pyzer-Knapp
2018 J jnl
Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks.
CoRR
Clyde Fare, Lukas Turcani, Edward O. Pyzer-Knapp
2017 A* conf
Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space.
ICML
José Miguel Hernández-Lobato, James Requeima, Edward O. Pyzer-Knapp, Alán Aspuru-Guzik