High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach T Pearce, M Zaki, A Brintrup, A Neely Proceedings of the 35th International Conference on Machine Learning, ICML, 2018 | 307 | 2018 |
Uncertainty in neural networks: Approximately bayesian ensembling T Pearce, F Leibfried, A Brintrup International conference on artificial intelligence and statistics, 234-244, 2020 | 280* | 2020 |
Supply chain data analytics for predicting supplier disruptions: a case study in complex asset manufacturing A Brintrup, J Pak, D Ratiney, T Pearce, P Wichmann, P Woodall, ... International Journal of Production Research 58 (11), 3330-3341, 2020 | 152 | 2020 |
Imitating Human Behaviour with Diffusion Models T Pearce, T Rashid, A Kanervisto, D Bignell, M Sun, R Georgescu, ... ICLR 2023, 2023 | 97 | 2023 |
Understanding softmax confidence and uncertainty T Pearce, A Brintrup, J Zhu arXiv preprint arXiv:2106.04972, 2021 | 78 | 2021 |
Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions T Pearce, R Tsuchida, M Zaki, A Brintrup, A Neely Uncertainty in Artificial Intelligence, UAI, 2019 | 59 | 2019 |
Bayesian Inference with Anchored Ensembles of Neural Networks, and Application to Exploration in Reinforcement Learning T Pearce, N Anastassacos, M Zaki, A Neely Exploration in Reinforcement Learning Workshop, ICML, 2018 | 37* | 2018 |
Recurrent neural networks for real-time distributed collaborative prognostics AS Palau, K Bakliwal, MH Dhada, T Pearce, AK Parlikad 2018 IEEE international conference on prognostics and health management …, 2018 | 27 | 2018 |
Counter-Strike Deathmatch with Large-Scale Behavioural Cloning T Pearce, J Zhu IEEE CoG 2022, 2022 | 24 | 2022 |
Bayesian Neural Network Ensembles T Pearce, M Zaki, A Neely Bayesian Deep Learning Workshop, NeurIPS, 2018 | 20* | 2018 |
Uncertainty in neural networks; bayesian ensembles, priors & prediction intervals T Pearce | 8 | 2020 |
TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play F Lin, S Huang, T Pearce, W Chen, WW Tu AAMAS 2023, 2023 | 7 | 2023 |
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks R Tsuchida, T Pearce, C Van Der Heide, F Roosta, M Gallagher AAAI, 2021 | 7 | 2021 |
Structured Weight Priors for Convolutional Neural Networks T Pearce, AYK Foong, A Brintrup Uncertainty & Robustness in Deep Learning Workshop, ICML, 2020 | 5 | 2020 |
Bayesian Autoencoders: Analysing and Fixing the Bernoulli likelihood for Out-of-Distribution Detection BX Yong, T Pearce, A Brintrup Uncertainty & Robustness in Deep Learning Workshop, ICML, 2020 | 5 | 2020 |
Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis T Pearce, JH Jeong, Y Jia, J Zhu NeurIPS 2022, 2022 | 4 | 2022 |
Coalitional Bargaining via Reinforcement Learning: An Application to Collaborative Vehicle Routing S Mak, L Xu, T Pearce, M Ostroumov, A Brintrup NeurIPS Cooperative AI Workshop, 2021 | 4 | 2021 |
DGPO: discovering multiple strategies with diversity-guided policy optimization W Chen, S Huang, Y Chiang, T Pearce, WW Tu, T Chen, J Zhu AAAI 2024, 2024 | 3 | 2024 |
Fair collaborative vehicle routing: A deep multi-agent reinforcement learning approach S Mak, L Xu, T Pearce, M Ostroumov, A Brintrup Transportation Research Part C: Emerging Technologies 157, 104376, 2023 | 2 | 2023 |
C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory T Luo, T Pearce, H Chen, J Chen, J Zhu arXiv preprint arXiv:2402.16349, 2024 | | 2024 |