| Decentralised learning in systems with many, many strategic agents D Mguni, J Jennings, EM de Cote Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 74 | 2018 |
| Learning in nonzero-sum stochastic games with potentials DH Mguni, Y Wu, Y Du, Y Yang, Z Wang, M Li, Y Wen, J Jennings, J Wang International Conference on Machine Learning, 7688-7699, 2021 | 47 | 2021 |
| Tumour heterogeneity promotes collective invasion and cancer metastatic dissemination A Hallou, J Jennings, AJ Kabla Royal Society Open Science 4 (8), 161007, 2017 | 41 | 2017 |
| Coordinating the crowd: Inducing desirable equilibria in non-cooperative systems D Mguni, J Jennings, SV Macua, E Sison, S Ceppi, EM De Cote arXiv preprint arXiv:1901.10923, 2019 | 39 | 2019 |
| Understanding causality with large language models: Feasibility and opportunities C Zhang, S Bauer, P Bennett, J Gao, W Gong, A Hilmkil, J Jennings, C Ma, ... arXiv preprint arXiv:2304.05524, 2023 | 26 | 2023 |
| Machine learning system A Tukiainen, D Kim, T Nicholson, M Tomczak, JEMDEC FLORES, ... US Patent App. 16/753,580, 2020 | 24 | 2020 |
| Rhino: Deep causal temporal relationship learning with history-dependent noise W Gong, J Jennings, C Zhang, N Pawlowski arXiv preprint arXiv:2210.14706, 2022 | 16 | 2022 |
| A causal AI suite for decision-making E Kiciman, EW Dillon, D Edge, A Foster, A Hilmkil, J Jennings, C Ma, ... NeurIPS 2022 Workshop on Causality for Real-world Impact, 2022 | 7 | 2022 |
| Answering causal questions with augmented llms N Pawlowski, J Vaughan, J Jennings, C Zhang | 6 | 2023 |
| Causal reasoning in the presence of latent confounders via neural admg learning M Ashman, C Ma, A Hilmkil, J Jennings, C Zhang arXiv preprint arXiv:2303.12703, 2023 | 6 | 2023 |
| A new computational model for multi-cellular biological systems JN Jennings | 6 | 2014 |
| Towards causal foundation model: on duality between causal inference and attention J Zhang, J Jennings, C Zhang, C Ma arXiv preprint arXiv:2310.00809, 2023 | 5 | 2023 |
| CO-BED: Information-theoretic contextual optimization via Bayesian experimental design DR Ivanova, J Jennings, T Rainforth, C Zhang, A Foster International Conference on Machine Learning, 14445-14464, 2023 | 5 | 2023 |
| Desta: A framework for safe reinforcement learning with markov games of intervention D Mguni, U Islam, Y Sun, X Zhang, J Jennings, A Sootla, C Yu, Z Wang, ... arXiv preprint arXiv:2110.14468, 2021 | 5 | 2021 |
| Bayesdag: Gradient-based posterior sampling for causal discovery Y Annadani, N Pawlowski, J Jennings, S Bauer, C Zhang, W Gong arXiv preprint arXiv:2307.13917, 2023 | 4 | 2023 |
| Using neural biomarkers to personalize dosing of vagus nerve stimulation A Berthon, L Wernisch, M Stoukidi, M Thornton, O Tessier-Lariviere, ... bioRxiv, 2023.08. 30.555487, 2023 | 3 | 2023 |
| Cancer Metastasis: collective invasion in heterogeneous multicellular systems A Hallou, J Jennings, A Kabla arXiv preprint arXiv:1501.00065, 2014 | 3 | 2014 |
| Efficient real-world testing of causal decision making via bayesian experimental design for contextual optimisation DR Ivanova, J Jennings, C Zhang, A Foster arXiv preprint arXiv:2207.05250, 2022 | 2 | 2022 |
| Instructions and guide: Causal insights for learning paths in education W Gong, D Smith, Z Wang, C Barton, S Woodhead, N Pawlowski, ... arXiv preprint arXiv:2208.12610, 2022 | 2 | 2022 |
| BayesDAG: Gradient-Based Posterior Inference for Causal Discovery Y Annadani, N Pawlowski, J Jennings, S Bauer, C Zhang, W Gong Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
