| Sigma: Simple greedy matching for aligning large knowledge bases S Lacoste-Julien, K Palla, A Davies, G Kasneci, T Graepel, Z Ghahramani Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013 | 209 | 2013 |
| Eddi: Efficient dynamic discovery of high-value information with partial vae C Ma, S Tschiatschek, K Palla, JM Hernández-Lobato, S Nowozin, ... arXiv preprint arXiv:1809.11142, 2018 | 149 | 2018 |
| An infinite latent attribute model for network data K Palla, D Knowles, Z Ghahramani arXiv preprint arXiv:1206.6416, 2012 | 138 | 2012 |
| A nonparametric variable clustering model K Palla, Z Ghahramani, D Knowles Advances in Neural Information Processing Systems 25, 2012 | 48 | 2012 |
| Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI T Papamarkou, M Skoularidou, K Palla, L Aitchison, J Arbel, D Dunson, ... Forty-first International Conference on Machine Learning, 2024 | 29* | 2024 |
| A comparative analysis of join algorithms using the hadoop map/reduce framework K Palla Master of science thesis. School of informatics, University of Edinburgh, 2009 | 26 | 2009 |
| Bayesian nonparametrics for sparse dynamic networks C Naik, F Caron, J Rousseau, YW Teh, K Palla Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 21 | 2022 |
| A reversible infinite HMM using normalised random measures D Knowles, Z Ghahramani, K Palla International Conference on Machine Learning, 1998-2006, 2014 | 20 | 2014 |
| Intraoperative prediction of postanaesthesia care unit hypotension K Palla, SL Hyland, K Posner, P Ghosh, B Nair, M Bristow, Y Paleva, ... British Journal of Anaesthesia 128 (4), 623-635, 2022 | 18 | 2022 |
| Relational learning and network modelling using infinite latent attribute models K Palla, DA Knowles, Z Ghahramani IEEE transactions on pattern analysis and machine intelligence 37 (2), 462-474, 2014 | 15 | 2014 |
| Odin: Optimal discovery of high-value information using model-based deep reinforcement learning S Zannone, JM Hernández-Lobato, C Zhang, K Palla ICML Real-world Sequential Decision Making Workshop, 2019 | 11 | 2019 |
| Framing machine learning opportunities for hypotension prediction in perioperative care: a socio-technical perspective: Socio-technical perspectives on hypotension prediction P Ghosh, KL Posner, SL Hyland, W Van Cleve, M Bristow, DR Long, ... ACM Transactions on Computer-Human Interaction 30 (5), 1-33, 2023 | 6 | 2023 |
| Harmonizing global voices: Culturally-aware models for enhanced content moderation AJ Chan, JLR García, F Silvestri, C O'Donnel, K Palla arXiv preprint arXiv:2312.02401, 2023 | 4 | 2023 |
| The Role of Context in the Prediction of Acute Hypotension in Critical Care N Prasad, K Palla SAIL: Symposium on Artificial Intelligence for Learning Health Systems 10, 2020, 2020 | 3 | 2020 |
| Topic modelling of authentication events in an enterprise computer network N Heard, K Palla, M Skoularidou 2016 IEEE Conference on Intelligence and Security Informatics (ISI), 190-192, 2016 | 3 | 2016 |
| A simulator for a mobile peer-to-peer database environment V Kantere, K Palla, K Patroumpas, T Sellis The Ninth International Conference on Mobile Data Management (mdm 2008), 223-224, 2008 | 2 | 2008 |
| A birth-death process for feature allocation K Palla, D Knowles, Z Ghahramani International Conference on Machine Learning, 2751-2759, 2017 | 1 | 2017 |
| A dependent partition-valued process for multitask clustering and time evolving network modelling K Palla, DA Knowles, Z Ghahramani arXiv preprint arXiv:1303.3265, 2013 | 1 | 2013 |
| Epistemic Uncertainty and Observation Noise with the Neural Tangent Kernel S Calvo-Ordoñez, K Palla, K Ciosek arXiv preprint arXiv:2409.03953, 2024 | | 2024 |
| Gathering data in a communication system C Zhang, RSB Nowozin, A Patel, DCM Belgrave, K Palla, A Thieme, ... US Patent 11,741,357, 2023 | | 2023 |
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleEmail verificata su eng.cam.ac.uk