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2020 – today
- 2022
[c2]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]Daniel Ward, Patrick Cannon, Mark Beaumont, Matteo Fasiolo, Sebastian M. Schmon:
Robust Neural Posterior Estimation and Statistical Model Criticism. NeurIPS 2022 - [i6]Joel Dyer, Patrick Cannon, J. Doyne Farmer, Sebastian M. Schmon:
Black-box Bayesian inference for economic agent-based models. CoRR abs/2202.00625 (2022) - [i5]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]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) - [i3]Jordan Langham-Lopez, Sebastian M. Schmon, Patrick Cannon:
High Performance Simulation for Scalable Multi-Agent Reinforcement Learning. CoRR abs/2207.03945 (2022) - [i2]Patrick Cannon, Daniel Ward, Sebastian M. Schmon:
Investigating the Impact of Model Misspecification in Neural Simulation-based Inference. CoRR abs/2209.01845 (2022) - [i1]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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