Andrei Paleyes
Andrei Paleyes
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Challenges in deploying machine learning: a survey of case studies
A Paleyes, RG Urma, ND Lawrence
ACM Computing Surveys (CSUR), 2020
Emulation of physical processes with emukit
A Paleyes, M Pullin, M Mahsereci, C McCollum, N Lawrence, J GonzŠlez
Second workshop on machine learning and the physical sciences, NeurIPS 2019, 2019
Causal bayesian optimization
V Aglietti, X Lu, A Paleyes, J GonzŠlez
International Conference on Artificial Intelligence and Statistics, 3155-3164, 2020
Automatic discovery of privacy-utility pareto fronts
B Avent, J Gonzalez, T Diethe, A Paleyes, B Balle
Privacy Enhancing Technologies Symposium, PETS 2020, 2019
Good practices for Bayesian optimization of high dimensional structured spaces
E Siivola, A Paleyes, J GonzŠlez, A Vehtari
Applied AI Letters 2 (2), e24, 2021
Trieste: Efficiently exploring the depths of black-box functions with TensorFlow
V Picheny, J Berkeley, HB Moss, H Stojic, U Granta, SW Ober, A Artemev, ...
arXiv preprint arXiv:2302.08436, 2023
Effectiveness and resource requirements of test, trace and isolate strategies for COVID in the UK
B He, S Zaidi, B Elesedy, M Hutchinson, A Paleyes, G Harling, ...
Royal Society open science 8 (3), 201491, 2021
Towards better data discovery and collection with flow-based programming
A Paleyes, C Cabrera, ND Lawrence
Data-centric AI workshop, NeurIPS 2021, 2021
Dataflow graphs as complete causal graphs
A Paleyes, S Guo, B Scholkopf, ND Lawrence
2023 IEEE/ACM 2nd International Conference on AI Engineering–Software†…, 2023
Real-world Machine Learning Systems: A survey from a Data-Oriented Architecture Perspective
C Cabrera, A Paleyes, P Thodoroff, ND Lawrence
arXiv preprint arXiv:2302.04810, 2023
DELVE global COVID-19 dataset
A Bhoopchand, A Paleyes, K Donkers, N Tomasev, U Paquet
Published June 2 2020, 2020
Desiderata for next generation of ML model serving
S Akoush, A Paleyes, A Van Looveren, C Cox
Workshop on Challenges in Deploying and Monitoring Machine Learning Systems†…, 2022
An empirical evaluation of flow based programming in the machine learning deployment context
A Paleyes, C Cabrera, ND Lawrence
Proceedings of the 1st International Conference on AI Engineering: Software†…, 2022
A penalisation method for batch multi-objective Bayesian optimisation with application in heat exchanger design
A Paleyes, HB Moss, V Picheny, P Zulawski, F Newman
Adaptive Experimental Design and Active Learning in the Real World Workshop†…, 2022
Causal fault localisation in dataflow systems
A Paleyes, ND Lawrence
Proceedings of the 3rd Workshop on Machine Learning and Systems, 140-147, 2023
Self-sustaining Software Systems (S4): Towards Improved Interpretability and Adaptation
C Cabrera, A Paleyes, ND Lawrence
arXiv preprint arXiv:2401.11370, 2024
Automated discovery of trade-off between utility, privacy and fairness in machine learning models
B Ficiu, ND Lawrence, A Paleyes
arXiv preprint arXiv:2311.15691, 2023
Emukit: A Python toolkit for decision making under uncertainty
A Paleyes, M Mahsereci, ND Lawrence
Proceedings of the Python in Science Conference, 2023
Towards Maintainable and Explainable AI Systems with Dataflow
A Paleyes
Can causality accelerate experimentation in software systems?
A Paleyes, HB Li, ND Lawrence
Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering†…, 2024
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