Edward Pyzer-Knapp

According to our database, Edward Pyzer-Knapp authored at least 23 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Hessian QM9: A quantum chemistry database of molecular Hessians in implicit solvents.

Nicholas J. Williams, Lara Kabalan, Ljiljana Stojanovic, Viktor Zolyomi, Edward O. Pyzer-Knapp

CoRR, 2024

Coalitions of Large Language Models Increase the Robustness of AI Agents.

Prattyush Mangal, Carol Mak, Theo Kanakis, Timothy Donovan, Dave Braines, Edward Pyzer-Knapp

CoRR, 2024

2023

Physics Inspired Approaches Towards Understanding Gaussian Processes.

Maximilian P. Niroomand, Luke Dicks, Edward O. Pyzer-Knapp, David J. Wales

CoRR, 2023

Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression.

Robert Allison, Anthony Stephenson, Samuel F, Edward O. Pyzer-Knapp

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Self-Focusing Virtual Screening with Active Design Space Pruning.

David E. Graff, Matteo Aldeghi, Joseph A. Morrone, Kirk E. Jordan, Edward O. Pyzer-Knapp, Connor W. Coley

J. Chem. Inf. Model., 2022

Roughness of Molecular Property Landscapes and Its Impact on Modellability.

Matteo Aldeghi, David E. Graff, Nathan C. Frey, Joseph A. Morrone, Edward O. Pyzer-Knapp, Kirk E. Jordan, Connor W. Coley

J. Chem. Inf. Model., 2022

Provably Reliable Large-Scale Sampling from Gaussian Processes.

Anthony Stephenson, Robert Allison, Edward Pyzer-Knapp

CoRR, 2022

A Principled Method for the Creation of Synthetic Multi-fidelity Data Sets.

Clyde Fare, Peter Fenner, Edward O. Pyzer-Knapp

CoRR, 2022

2021

SMC samplers for Bayesian Optimisation and Discovery of Additive Kernel Structure.

Aikaterini Chatzopoulou, Ángel F. García-Fernández, Edward Pyzer-Knapp, Simon Maskell

Proceedings of the 24th IEEE International Conference on Information Fusion, 2021

Heterogeneous Computing Systems for Complex Scientific Discovery Workflows.

Christoph Hagleitner, Dionysios Diamantopoulos, Burkhard Ringlein, Constantinos Evangelinos, Charles R. Johns, Rong N. Chang, Bruce D'Amora, James A. Kahle, James C. Sexton, Michael Johnston, Edward Pyzer-Knapp, Chris Ward

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

2020

A Fast Parallel Particle Filter for Shared Memory Systems.

Alessandro Varsi, Jack Taylor, Lykourgos Kekempanos, Edward Pyzer-Knapp, Simon Maskell

IEEE Signal Process. Lett., 2020

Using Bayesian Optimization to Accelerate Virtual Screening for the Discovery of Therapeutics Appropriate for Repurposing for COVID-19.

Edward O. Pyzer-Knapp

CoRR, 2020

Modelling Mobile Signal Strength by Combining Geospatial Big Data and Artificial Intelligence.

Paolo Fraccaro, Matt Benatan, Katharina Reusch, Clyde Fare, Blair Edwards, Edward Pyzer-Knapp

Proceedings of the ICVISP 2020: 4th International Conference on Vision, 2020

Privacy-Preserving Gaussian Process Regression - A Modular Approach to the Application of Homomorphic Encryption.

Peter Fenner, Edward Pyzer-Knapp

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Utilizing Machine Learning for Efficient Parameterization of Coarse Grained Molecular Force Fields.

James L. McDonagh, Ardita Shkurti, David J. Bray, Richard L. Anderson, Edward O. Pyzer-Knapp

J. Chem. Inf. Model., 2019

Fully Bayesian Recurrent Neural Networks for Safe Reinforcement Learning.

Matt Benatan, Edward O. Pyzer-Knapp

CoRR, 2019

A Fast Machine Learning Workflow for Rapid Phenotype Prediction from Whole Shotgun Metagenomes.

Anna Paola Carrieri, Will P. M. Rowe, Martyn D. Winn, Edward O. Pyzer-Knapp

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Bayesian optimization for accelerated drug discovery.

Edward O. Pyzer-Knapp

IBM J. Res. Dev., 2018

Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks.

Clyde Fare, Lukas Turcani, Edward O. Pyzer-Knapp

CoRR, 2018

Dynamic Control of Explore/Exploit Trade-Off In Bayesian Optimization.

Dipti Jasrasaria, Edward O. Pyzer-Knapp

CoRR, 2018

Efficient and Scalable Batch Bayesian Optimization Using K-Means.

Matthew Groves, Edward O. Pyzer-Knapp

CoRR, 2018

2017

Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space.

José Miguel Hernández-Lobato, James Requeima, Edward O. Pyzer-Knapp, Alán Aspuru-Guzik

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

The quantum chemical search for novel materials and the issue of data processing: The InfoMol project.

Hans Peter Lüthi, Stefan N. Heinen, Gisbert Schneider, Andreas Glöss, Martin P. Brändle, Rollin A. King, Edward Pyzer-Knapp, Fahhad H. Alharbi, Sabre Kais

J. Comput. Sci., 2016