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Henry B Moss
Henry B Moss
Early Career Fellow, University of Cambridge
Verified email at cam.ac.uk
Title
Cited by
Cited by
Year
BOSS: Bayesian Optimization over String Spaces
HB Moss, D Beck, J Gonzalez, DS Leslie, P Rayson
Advances in Neural Information Processing Systems (NeurIPS) 2020, 2020
692020
Boffin tts: Few-shot speaker adaptation by bayesian optimization
HB Moss, V Aggarwal, N Prateek, J González, R Barra-Chicote
The International Conference on Acoustics, Speech and Signal Processing …, 2020
572020
Using JK fold Cross Validation to Reduce Variance When Tuning NLP Models
HB Moss, DS Leslie, P Rayson
The International Conference on Computational Linguisitics (COLING) 2018, 2018
432018
MUMBO: Multi-task Max-value Bayesian Optimization
HB Moss, DS Leslie, P Rayson
The European Conference on Machine Learning (ECML) 2020, 2020
392020
Scalable Thompson Sampling using Sparse Gaussian Process Models
S Vakili, HB Moss, V Picheny, A Artemev
Advances in Neural Information Processing Systems (NeurIPS) 2021, 2021
362021
GIBBON: General-purpose Information-Based Bayesian OptimisatioN
HB Moss, DS Leslie, J Gonzalez, P Rayson
Journal of Machine Learning Research (JMLR) 2021, 2021
312021
Data-driven discovery of molecular photoswitches with multioutput Gaussian processes
RR Griffiths, JL Greenfield, AR Thawani, AR Jamasb, HB Moss, ...
Chemical Science 13 (45), 13541-13551, 2022
30*2022
Gaussian Process Molecule Property Prediction with FlowMO
HB Moss, RR Griffiths
ML4 Molecules Workshop at NeurIPS 2020, 2020
27*2020
Gauche: A library for gaussian processes in chemistry
RR Griffiths, L Klarner, H Moss, A Ravuri, S Truong, Y Du, S Stanton, ...
Advances in Neural Information Processing Systems 36, 2024
26*2024
Bayesian Quantile and Expectile Optimisation
V Picheny, H Moss, L Torossian, N Durrande
The 38th Conference on Uncertainty in Artificial Intelligence (UAI), 2022
212022
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
18*2023
BOSH: Bayesian Optimization by Sampling Hierarchically
HB Moss, DS Leslie, P Rayson
Real World Experiment Design and Active Learning Workshop at ICML 2020, 2020
122020
A Case for Domain Expert Dataset Curation in Machine-Learning Enabled Chemistry
AR Thawani, RR Griffiths, AR Jamasb, HB Moss, A Bourached, P Jones, ...
11*
FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms
HB Moss, A Moore, DS Leslie, P Rayson
The Conference of the Association for Computational Linguistics (ACL) 2019, 2019
92019
Bayesian optimisation for additive screening and yield improvements in chemical reactions–beyond one-hot encoding
B Ranković, RR Griffiths, HB Moss, P Schwaller
82023
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation
HB Moss, SW Ober, V Picheny
25th International Conference on Artificial Intelligence and Statistics …, 2023
82023
Fantasizing with dual GPs in Bayesian optimization and active learning
PE Chang, P Verma, ST John, V Picheny, H Moss, A Solin
arXiv preprint arXiv:2211.01053, 2022
5*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
Real World Experiment Design and Active Learning Workshop at ICML 2022, 2022
52022
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning
AX Yang, L Aitchison, HB Moss
arXiv preprint arXiv:2302.11533, 2023
42023
Information-theoretic Inducing Point Placement for High-throughput Bayesian Optimisation
HB Moss, SW Ober, V Picheny
Real World Experiment Design and Active Learning Workshop at ICML 2022, 2022
42022
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