| 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 | 91 | 2020 |
| 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 | 74 | 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 | 53* | 2024 |
| MUMBO: Multi-task Max-value Bayesian Optimization HB Moss, DS Leslie, P Rayson The European Conference on Machine Learning (ECML) 2020, 2020 | 48 | 2020 |
| 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 | 47 | 2018 |
| 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 | 46 | 2021 |
| GIBBON: General-purpose Information-Based Bayesian OptimisatioN HB Moss, DS Leslie, J Gonzalez, P Rayson Journal of Machine Learning Research (JMLR) 2021, 2021 | 45 | 2021 |
| Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow H Moss, V Picheny, H Stojic, SW Ober, A Artemev, A Paleyes, S Vakili, ... NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty, 2024 | 33* | 2024 |
| Gaussian Process Molecule Property Prediction with FlowMO HB Moss, RR Griffiths ML4 Molecules Workshop at NeurIPS 2020, 2020 | 32* | 2020 |
| 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 | 31 | 2022 |
| Bayesian Quantile and Expectile Optimisation V Picheny, H Moss, L Torossian, N Durrande The 38th Conference on Uncertainty in Artificial Intelligence (UAI), 2022 | 30 | 2022 |
| 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 | 26 | 2023 |
| The photoswitch dataset: A molecular machine learning benchmark for the advancement of synthetic chemistry AR Thawani, RR Griffiths, A Jamasb, A Bourached, P Jones, ... | 19 | 2020 |
| Bayesian optimisation for additive screening and yield improvements–beyond one-hot encoding B Ranković, RR Griffiths, HB Moss, P Schwaller Digital Discovery 3 (4), 654-666, 2024 | 18* | 2024 |
| ICASSP 2020-2020 IEEE International Conference on Acoustics HB Moss, V Aggarwal, N Prateek, J González, R Barra-Chicote Speech and Signal Processing (ICASSP), 7639-7643, 2020 | 17 | 2020 |
| 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 | 12* | 2022 |
| BOSH: Bayesian Optimization by Sampling Hierarchically HB Moss, DS Leslie, P Rayson Real World Experiment Design and Active Learning Workshop at ICML 2020, 2020 | 11 | 2020 |
| 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 | 9 | 2019 |
| 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 | 8 | 2022 |
Ryan-Rhys GriffithsFutureHouse | University of CambridgeVerified email at futurehouse.org
