Tim Pearce
Tim Pearce
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Cited by
Cited by
Uncertainty in neural networks: Approximately bayesian ensembling
T Pearce, F Leibfried, A Brintrup
International conference on artificial intelligence and statistics, 234-244, 2020
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
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
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
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
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 managementá…, 2018
Bayesian Neural Network Ensembles
T Pearce, M Zaki, A Neely
Bayesian Deep Learning Workshop, NeurIPS, 2018
Understanding softmax confidence and uncertainty
T Pearce, A Brintrup, J Zhu
arXiv preprint arXiv:2106.04972, 2021
Structured Weight Priors for Convolutional Neural Networks
T Pearce, AYK Foong, A Brintrup
Uncertainty & Robustness in Deep Learning Workshop, ICML, 2020
Counter-Strike Deathmatch with Large-Scale Behavioural Cloning
T Pearce, J Zhu
IEEE CoG 2022 // Offline RL Workshop, NeurIPS 2021, 2021
Uncertainty in neural networks; bayesian ensembles, priors & prediction intervals
T Pearce
University of Cambridge, 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
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
Censored Quantile Regression Neural Networks
T Pearce, JH Jeong, Y Jia, J Zhu
arXiv preprint arXiv:2205.13496, 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
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