| Black-box Bayesian inference for economic agent-based models J Dyer, P Cannon, JD Farmer, S Schmon arXiv preprint arXiv:2202.00625, 2022 | 28 | 2022 |
| Generalized Posteriors in Approximate Bayesian Computation SM Schmon, PW Cannon, J Knoblauch arXiv preprint arXiv:2011.08644, 2020 | 23 | 2020 |
| Robust Neural Posterior Estimation and Statistical Model Criticism D Ward, P Cannon, M Beaumont, M Fasiolo, SM Schmon Neural Information Processing Systems 36, 2022 | 18 | 2022 |
| Investigating the Impact of Model Misspecification in Neural Simulation-based Inference P Cannon, D Ward, SM Schmon arXiv preprint arXiv:2209.01845, 2022 | 16 | 2022 |
| Approximate Bayesian Computation with Path Signatures J Dyer, P Cannon, SM Schmon arXiv preprint arXiv:2106.12555, 2021 | 16 | 2021 |
| Calibrating Agent-based Models to Microdata with Graph Neural Networks J Dyer, P Cannon, JD Farmer, SM Schmon arXiv preprint arXiv:2206.07570, 2022 | 14 | 2022 |
| Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation J Dyer, P Cannon, SM Schmon AISTATS, 2022, 2022 | 8 | 2022 |
| Deep Signature Statistics for Likelihood-free Time-series Models J Dyer, PW Cannon, SM Schmon ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit …, 2021 | 8 | 2021 |
| Black-box Bayesian inference for agent-based models J Dyer, P Cannon, JD Farmer, SM Schmon Journal of Economic Dynamics and Control, 104827, 2024 | | 2024 |
| High Performance Simulation for Scalable Multi-Agent Reinforcement Learning J Langham-Lopez, SM Schmon, P Cannon arXiv preprint arXiv:2207.03945, 2022 | | 2022 |
| A Particle Markov Chain Monte Carlo Approach to Coalescent Inference PW Cannon University of Bristol, 2019 | | 2019 |
Sebastian M SchmonSenior Staff Machine Learning Engineer at Altos LabsVerified email at stats.ox.ac.uk
