Lawrence, Neil D.

Challenges in deploying machine learning: A survey of case studies

Paleyes, A., Urma, R.-G., & Lawrence, N. D. (2023) · ACM Computing Surveys

Software Engineering Techniques and PracticesArtificial Intelligence Applications

Cited by 638

Bottom-up data Trusts: disturbing the ‘one size fits all’ approach to data governance

Delacroix, S., & Lawrence, N. D. (2019) · International Data Privacy Law

Digitalization, Law, and RegulationEthics and Social Impacts of AI

Cited by 179

Topologically-constrained latent variable models

Urtasun, R., Fleet, D. J., Geiger, A., Popović, J., Darrell, T. J., & Lawrence, N. D. (2008) · Proceedings of the 25th international conference on Machine learning - ICML '08

Gaussian Processes and Bayesian InferenceHuman Motion and Animation

Cited by 125

A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression

Kalaitzis, A. A., & Lawrence, N. D. (2011) · BMC Bioinformatics

Gene expression and cancer classificationGene Regulatory Network Analysis

Cited by 91

Detecting periodicities with Gaussian processes

Durrande, N., Hensman, J., Rattray, M., & Lawrence, N. D. (2016) · PeerJ Computer Science

Gaussian Processes and Bayesian InferenceMathematical Analysis and Transform Methods

Cited by 39

Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experiment

Cortes, C., & Lawrence, N. D. (2021) · arXiv

scientometrics and bibliometrics researchPublishing and Scholarly Communication

Cited by 15

Requirements Are All You Need: The Final Frontier for End-User Software Engineering

Robinson, D., Cabrera, C., Gordon, A. D., Lawrence, N. D., & Mennen, L. (2025) · ACM Transactions on Software Engineering and Methodology

Software Engineering Techniques and PracticesSpreadsheets and End-User Computing

Cited by 12

Bottom-up data Trusts: disturbing the ‘one size fits all’ approach to data governance

Delacroix, S., & Lawrence, N. (2018) · SSRN Electronic Journal

Digitalization, Law, and RegulationDiverse Legal and Medical Studies

Cited by 11

Code Roulette: How Prompt Variability Affects LLM Code Generation

Paleyes, A., Robinson, D., Sendyka, R., Cabrera, C., & Lawrence, N. D. (2026) · Proceedings of the 3rd International Workshop on Large Language Models For Code

Software Engineering ResearchTopic Modeling

Cited by 8