Tim Pearce

According to our database, Tim Pearce authored at least 30 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

External Nonfinancial Measures in Substantive Analytical Procedures: Contributions of Weather Information.

Kyunghee Yoon, Alexander Kogan, Miklos A. Vasarhelyi, Tim Pearce

J. Inf. Syst., 2024

Scaling Laws for Pre-training Agents and World Models.

Tim Pearce, Tabish Rashid, David Bignell, Raluca Georgescu, Sam Devlin, Katja Hofmann

CoRR, 2024

Reconciling Kaplan and Chinchilla Scaling Laws.

Tim Pearce, Jinyeop Song

CoRR, 2024

Diffusion for World Modeling: Visual Details Matter in Atari.

Eloi Alonso, Adam Jelley, Vincent Micheli, Anssi Kanervisto, Amos J. Storkey, Tim Pearce, François Fleuret

CoRR, 2024

C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory.

Tianjiao Luo, Tim Pearce, Huayu Chen, Jianfei Chen, Jun Zhu

CoRR, 2024

DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization.

Wentse Chen, Shiyu Huang, Yuan Chiang, Tim Pearce, Wei-Wei Tu, Ting Chen, Jun Zhu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Fair collaborative vehicle routing: A deep multi-agent reinforcement learning approach.

Stephen Mak, Liming Xu, Tim Pearce, Michael Ostroumov, Alexandra Brintrup

CoRR, 2023

Coalitional Bargaining via Reinforcement Learning: An Application to Collaborative Vehicle Routing.

Stephen Mak, Liming Xu, Tim Pearce, Michael Ostroumov, Alexandra Brintrup

CoRR, 2023

Imitating Human Behaviour with Diffusion Models.

Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin

Proceedings of the Eleventh International Conference on Learning Representations, 2023

TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play.

Fanqi Lin, Shiyu Huang, Tim Pearce, Wenze Chen, Wei-Wei Tu

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

Censored Quantile Regression Neural Networks.

Tim Pearce, Jong-Hyeon Jeong, Yichen Jia, Jun Zhu

CoRR, 2022

Fuzzy Inference for Well Log Lithology Classification.

Sam Fetherstonhaugh, John Martin, Tim Pearce, Neil Mac Parthaláin, Otar Akanyeti

Proceedings of the Advances in Computational Intelligence Systems, 2022

Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis.

Tim Pearce, Jong-Hyeon Jeong, Yichen Jia, Jun Zhu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Counter-Strike Deathmatch with Large-Scale Behavioural Cloning.

Tim Pearce, Jun Zhu

Proceedings of the IEEE Conference on Games, CoG 2022, Beijing, 2022

2021

Bayesian Autoencoders: Analysing and Fixing the Bernoulli likelihood for Out-of-Distribution Detection.

Bang Xiang Yong, Tim Pearce, Alexandra Brintrup

CoRR, 2021

Understanding Softmax Confidence and Uncertainty.

Tim Pearce, Alexandra Brintrup, Jun Zhu

CoRR, 2021

Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks.

Russell Tsuchida, Tim Pearce, Christopher van der Heide, Fred Roosta, Marcus Gallagher

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Uncertainty in neural networks: Bayesian ensembles, priors & prediction intervals.

Tim Pearce

PhD thesis, 2020

Supply chain data analytics for predicting supplier disruptions: a case study in complex asset manufacturing.

Alexandra Brintrup, Johnson Pak, David Ratiney, Tim Pearce, Pascal Wichmann, Philip Woodall, Duncan C. McFarlane

Int. J. Prod. Res., 2020

Structured Weight Priors for Convolutional Neural Networks.

Tim Pearce, Andrew Y. K. Foong, Alexandra Brintrup

CoRR, 2020

Universal access for object-based media experiences.

Juliette Carter, Rajiv Ramdhany, Mark Lomas, Tim Pearce, James Shephard, Michael Sparks

Proceedings of the 11th ACM Multimedia Systems Conference, 2020

Uncertainty in Neural Networks: Approximately Bayesian Ensembling.

Tim Pearce, Felix Leibfried, Alexandra Brintrup

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions.

Tim Pearce, Mohamed Zaki, Alexandra Brintrup, Andy Neely

CoRR, 2019

Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions.

Tim Pearce, Russell Tsuchida, Mohamed Zaki, Alexandra Brintrup, Andy Neely

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

2018

Bayesian Neural Network Ensembles.

Tim Pearce, Mohamed Zaki, Andy Neely

CoRR, 2018

Uncertainty in Neural Networks: Bayesian Ensembling.

Tim Pearce, Mohamed Zaki, Alexandra Brintrup, Andy Neely

CoRR, 2018

Bayesian Inference with Anchored Ensembles of Neural Networks, and Application to Reinforcement Learning.

Tim Pearce, Nicolas Anastassacos, Mohamed Zaki, Andy Neely

CoRR, 2018

Recurrent Neural Networks for real-time distributed collaborative prognostics.

Adrià Salvador Palau, Kshitij Bakliwal, Maharshi Harshadbhai Dhada, Tim Pearce, Ajith Kumar Parlikad

Proceedings of the 2018 IEEE International Conference on Prognostics and Health Management, 2018

High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach.

Tim Pearce, Alexandra Brintrup, Mohamed Zaki, Andy Neely

Proceedings of the 35th International Conference on Machine Learning, 2018

2014

Musculoskeletal Symptoms Amongst Clinical Radiologists and the Implications of Reporting Environment Ergonomics - A Multicentre Questionnaire Study.

Jonathan C. L. Rodrigues, Steven Morgan, Katharine Augustine, Gavin Clague, Tim Pearce, Adrian Pollentine, Adam Wallis, David Wilson, Paul McCoubrie

J. Digit. Imaging, 2014