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ORCIDTim Pearce
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2020 – today
- 2024
[j3]Kyunghee Yoon
, Alexander Kogan, Miklos A. Vasarhelyi, Tim Pearce:
External Nonfinancial Measures in Substantive Analytical Procedures: Contributions of Weather Information. J. Inf. Syst. 38(2): 143-162 (2024)- [c12]Wentse Chen, Shiyu Huang, Yuan Chiang, Tim Pearce, Wei-Wei Tu, Ting Chen, Jun Zhu:
DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization. AAAI 2024: 11390-11398 - [i17]Tianjiao Luo, Tim Pearce, Huayu Chen, Jianfei Chen, Jun Zhu:
C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory. CoRR abs/2402.16349 (2024) - [i16]Eloi Alonso, Adam Jelley, Vincent Micheli, Anssi Kanervisto, Amos J. Storkey, Tim Pearce, François Fleuret:
Diffusion for World Modeling: Visual Details Matter in Atari. CoRR abs/2405.12399 (2024) - [i15]Tim Pearce, Jinyeop Song:
Reconciling Kaplan and Chinchilla Scaling Laws. CoRR abs/2406.12907 (2024) - 2023
- [c11]Fanqi Lin, Shiyu Huang, Tim Pearce, Wenze Chen, Wei-Wei Tu:
TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play. AAMAS 2023: 67-76 - [c10]Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin:
Imitating Human Behaviour with Diffusion Models. ICLR 2023 - [i14]Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin:
Imitating Human Behaviour with Diffusion Models. CoRR abs/2301.10677 (2023) - [i13]Fanqi Lin, Shiyu Huang, Tim Pearce, Wenze Chen, Wei-Wei Tu:
TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play. CoRR abs/2302.07515 (2023) - [i12]Stephen Mak, Liming Xu, Tim Pearce, Michael Ostroumov, Alexandra Brintrup:
Coalitional Bargaining via Reinforcement Learning: An Application to Collaborative Vehicle Routing. CoRR abs/2310.17458 (2023) - [i11]Stephen Mak, Liming Xu, Tim Pearce, Michael Ostroumov, Alexandra Brintrup:
Fair collaborative vehicle routing: A deep multi-agent reinforcement learning approach. CoRR abs/2310.17485 (2023) - 2022
- [c9]Tim Pearce, Jun Zhu:
Counter-Strike Deathmatch with Large-Scale Behavioural Cloning. CoG 2022: 104-111 - [c8]Tim Pearce, Jong-Hyeon Jeong, Yichen Jia, Jun Zhu:
Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis. NeurIPS 2022 - [c7]Sam Fetherstonhaugh, John Martin, Tim Pearce, Neil Mac Parthaláin, Otar Akanyeti:
Fuzzy Inference for Well Log Lithology Classification. UKCI 2022: 89-102 - [i10]Tim Pearce, Jong-Hyeon Jeong, Yichen Jia, Jun Zhu:
Censored Quantile Regression Neural Networks. CoRR abs/2205.13496 (2022) - 2021
- [c6]Russell Tsuchida, Tim Pearce, Christopher van der Heide, Fred Roosta, Marcus Gallagher:
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. AAAI 2021: 9967-9977 - [i9]Tim Pearce, Jun Zhu:
Counter-Strike Deathmatch with Large-Scale Behavioural Cloning. CoRR abs/2104.04258 (2021) - [i8]Tim Pearce, Alexandra Brintrup, Jun Zhu:
Understanding Softmax Confidence and Uncertainty. CoRR abs/2106.04972 (2021) - [i7]Bang Xiang Yong, Tim Pearce, Alexandra Brintrup:
Bayesian Autoencoders: Analysing and Fixing the Bernoulli likelihood for Out-of-Distribution Detection. CoRR abs/2107.13304 (2021) - 2020
- [b1]Tim Pearce:
Uncertainty in neural networks: Bayesian ensembles, priors & prediction intervals. University of Cambridge, UK, 2020 - [j2]Alexandra Brintrup, Johnson Pak, David Ratiney, Tim Pearce, Pascal Wichmann, Philip Woodall, Duncan C. McFarlane:
Supply chain data analytics for predicting supplier disruptions: a case study in complex asset manufacturing. Int. J. Prod. Res. 58(11): 3330-3341 (2020) - [c5]Tim Pearce, Felix Leibfried, Alexandra Brintrup:
Uncertainty in Neural Networks: Approximately Bayesian Ensembling. AISTATS 2020: 234-244 - [c4]Juliette Carter, Rajiv Ramdhany, Mark Lomas, Tim Pearce, James Shephard, Michael Sparks:
Universal access for object-based media experiences. MMSys 2020: 382-385 - [i6]Russell Tsuchida, Tim Pearce, Christopher van der Heide, Fred Roosta, Marcus Gallagher:
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. CoRR abs/2002.08517 (2020) - [i5]Tim Pearce, Andrew Y. K. Foong, Alexandra Brintrup:
Structured Weight Priors for Convolutional Neural Networks. CoRR abs/2007.14235 (2020)
2010 – 2019
- 2019
- [c3]Tim Pearce, Russell Tsuchida, Mohamed Zaki, Alexandra Brintrup, Andy Neely:
Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions. UAI 2019: 134-144 - [i4]Tim Pearce, Mohamed Zaki, Alexandra Brintrup, Andy Neely:
Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions. CoRR abs/1905.06076 (2019) - 2018
- [c2]Tim Pearce, Alexandra Brintrup, Mohamed Zaki, Andy Neely:
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach. ICML 2018: 4072-4081 - [c1]Adrià Salvador Palau, Kshitij Bakliwal, Maharshi Harshadbhai Dhada, Tim Pearce, Ajith Kumar Parlikad:
Recurrent Neural Networks for real-time distributed collaborative prognostics. ICPHM 2018: 1-8 - [i3]Tim Pearce, Nicolas Anastassacos, Mohamed Zaki, Andy Neely:
Bayesian Inference with Anchored Ensembles of Neural Networks, and Application to Reinforcement Learning. CoRR abs/1805.11324 (2018) - [i2]Tim Pearce, Mohamed Zaki, Alexandra Brintrup, Andy Neely:
Uncertainty in Neural Networks: Bayesian Ensembling. CoRR abs/1810.05546 (2018) - [i1]Tim Pearce, Mohamed Zaki, Andy Neely:
Bayesian Neural Network Ensembles. CoRR abs/1811.12188 (2018) - 2014
- [j1]Jonathan C. L. Rodrigues, Steven Morgan, Katharine Augustine, Gavin Clague, Tim Pearce, Adrian Pollentine, Adam Wallis, David Wilson, Paul McCoubrie:
Musculoskeletal Symptoms Amongst Clinical Radiologists and the Implications of Reporting Environment Ergonomics - A Multicentre Questionnaire Study. J. Digit. Imaging 27(2): 255-261 (2014)
Coauthor Index
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last updated on 2024-11-13 23:47 CET by the dblp team
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