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ORCIDEdward Pyzer-Knapp
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2020 – today
- 2024
[i13]Prattyush Mangal, Carol Mak, Theo Kanakis, Timothy Donovan, Dave Braines, Edward Pyzer-Knapp:
Coalitions of Large Language Models Increase the Robustness of AI Agents. CoRR abs/2408.01380 (2024)- [i12]Nicholas J. Williams, Lara Kabalan, Ljiljana Stojanovic
, Viktor Zolyomi, Edward O. Pyzer-Knapp:
Hessian QM9: A quantum chemistry database of molecular Hessians in implicit solvents. CoRR abs/2408.08006 (2024) - 2023
- [c7]Robert Allison, Anthony Stephenson, Samuel F, Edward O. Pyzer-Knapp:
Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression. NeurIPS 2023 - [i11]Maximilian P. Niroomand, Luke Dicks, Edward O. Pyzer-Knapp, David J. Wales:
Physics Inspired Approaches Towards Understanding Gaussian Processes. CoRR abs/2305.10748 (2023) - [i10]Robert Allison, Anthony Stephenson, Samuel F, Edward Pyzer-Knapp:
Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression. CoRR abs/2306.14731 (2023) - 2022
- [j6]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): 3854-3862 (2022) - [j5]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): 4660-4671 (2022) - [i9]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 abs/2205.01753 (2022) - [i8]Clyde Fare, Peter Fenner, Edward O. Pyzer-Knapp:
A Principled Method for the Creation of Synthetic Multi-fidelity Data Sets. CoRR abs/2208.05667 (2022) - [i7]Anthony Stephenson, Robert Allison, Edward Pyzer-Knapp:
Provably Reliable Large-Scale Sampling from Gaussian Processes. CoRR abs/2211.08036 (2022) - 2021
- [c6]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:
Heterogeneous Computing Systems for Complex Scientific Discovery Workflows. DATE 2021: 13-18 - [c5]Aikaterini Chatzopoulou, Ángel F. García-Fernández, Edward Pyzer-Knapp, Simon Maskell:
SMC samplers for Bayesian Optimisation and Discovery of Additive Kernel Structure. FUSION 2021: 1-8 - 2020
- [j4]Alessandro Varsi, Jack Taylor, Lykourgos Kekempanos, Edward Pyzer-Knapp, Simon Maskell:
A Fast Parallel Particle Filter for Shared Memory Systems. IEEE Signal Process. Lett. 27: 1570-1574 (2020) - [c4]Peter Fenner, Edward Pyzer-Knapp:
Privacy-Preserving Gaussian Process Regression - A Modular Approach to the Application of Homomorphic Encryption. AAAI 2020: 3866-3873 - [c3]Paolo Fraccaro, Matt Benatan, Katharina Reusch, Clyde Fare, Blair Edwards, Edward Pyzer-Knapp:
Modelling Mobile Signal Strength by Combining Geospatial Big Data and Artificial Intelligence. ICVISP 2020: 49:1-49:5 - [i6]Peter Fenner, Edward O. Pyzer-Knapp:
Privacy-Preserving Gaussian Process Regression - A Modular Approach to the Application of Homomorphic Encryption. CoRR abs/2001.10893 (2020) - [i5]Edward O. Pyzer-Knapp:
Using Bayesian Optimization to Accelerate Virtual Screening for the Discovery of Therapeutics Appropriate for Repurposing for COVID-19. CoRR abs/2005.07121 (2020)
2010 – 2019
- 2019
- [j3]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): 4278-4288 (2019) - [c2]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: 9434-9439 - [i4]Matt Benatan, Edward O. Pyzer-Knapp:
Fully Bayesian Recurrent Neural Networks for Safe Reinforcement Learning. CoRR abs/1911.03308 (2019) - 2018
- [j2]Edward O. Pyzer-Knapp:
Bayesian optimization for accelerated drug discovery. IBM J. Res. Dev. 62(6): 2:1-2:7 (2018) - [i3]Matthew Groves, Edward O. Pyzer-Knapp:
Efficient and Scalable Batch Bayesian Optimization Using K-Means. CoRR abs/1806.01159 (2018) - [i2]Dipti Jasrasaria, Edward O. Pyzer-Knapp:
Dynamic Control of Explore/Exploit Trade-Off In Bayesian Optimization. CoRR abs/1807.01279 (2018) - [i1]Clyde Fare, Lukas Turcani, Edward O. Pyzer-Knapp:
Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks. CoRR abs/1809.06334 (2018) - 2017
- [c1]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: 1470-1479 - 2016
- [j1]Hans Peter Lüthi, Stefan N. Heinen, Gisbert Schneider, Andreas Glöss, Martin P. Brändle, Rollin A. King, Edward Pyzer-Knapp, Fahhad H. Alharbi, Sabre Kais:
The quantum chemical search for novel materials and the issue of data processing: The InfoMol project. J. Comput. Sci. 15: 65-73 (2016)
Coauthor Index
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