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Patrick Cannon

Patrick W. Cannon

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2022
[c2]
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  - conf/aistats/DyerCS22
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  - https://dblp.org/rec/conf/aistats/DyerCS22
Joel Dyer, Patrick W. Cannon, Sebastian M. Schmon:
Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation. AISTATS 2022: 11131-11144
[c1]
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  - conf/nips/WardCBFS22
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Daniel Ward, Patrick Cannon, Mark Beaumont, Matteo Fasiolo, Sebastian M. Schmon:
Robust Neural Posterior Estimation and Statistical Model Criticism. NeurIPS 2022
[i6]
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  - journals/corr/abs-2202-00625
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Joel Dyer, Patrick Cannon, J. Doyne Farmer, Sebastian M. Schmon:
Black-box Bayesian inference for economic agent-based models. CoRR abs/2202.00625 (2022)
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  - journals/corr/abs-2202-11585
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Joel Dyer, Patrick Cannon, Sebastian M. Schmon:
Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation. CoRR abs/2202.11585 (2022)
[i4]
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  - journals/corr/abs-2206-07570
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Joel Dyer, Patrick Cannon, J. Doyne Farmer, Sebastian M. Schmon:
Calibrating Agent-based Models to Microdata with Graph Neural Networks. CoRR abs/2206.07570 (2022)
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  - journals/corr/abs-2207-03945
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Jordan Langham-Lopez, Sebastian M. Schmon, Patrick Cannon:
High Performance Simulation for Scalable Multi-Agent Reinforcement Learning. CoRR abs/2207.03945 (2022)
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  - journals/corr/abs-2209-01845
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Patrick Cannon, Daniel Ward, Sebastian M. Schmon:
Investigating the Impact of Model Misspecification in Neural Simulation-based Inference. CoRR abs/2209.01845 (2022)
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  - journals/corr/abs-2210-06564
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Daniel Ward, Patrick Cannon, Mark Beaumont, Matteo Fasiolo, Sebastian M. Schmon:
Robust Neural Posterior Estimation and Statistical Model Criticism. CoRR abs/2210.06564 (2022)

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