Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation. - Joel Dyer; Patrick W. Cannon; Sebastian M. Schmon (AISTATS, 2022)

Robust Neural Posterior Estimation and Statistical Model Criticism. - Daniel Ward; Patrick Cannon; Mark Beaumont; Matteo Fasiolo; Sebastian M. Schmon (NeurIPS, 2022)

Black-box Bayesian inference for economic agent-based models. - Joel Dyer; Patrick Cannon; J. Doyne Farmer; Sebastian M. Schmon (CoRR, 2022)

Calibrating Agent-based Models to Microdata with Graph Neural Networks. - Joel Dyer; Patrick Cannon; J. Doyne Farmer; Sebastian M. Schmon (CoRR, 2022)

High Performance Simulation for Scalable Multi-Agent Reinforcement Learning. - Jordan Langham-Lopez; Sebastian M. Schmon; Patrick Cannon (CoRR, 2022)

Investigating the Impact of Model Misspecification in Neural Simulation-based Inference. - Patrick Cannon; Daniel Ward; Sebastian M. Schmon (CoRR, 2022)

Approximate Bayesian Computation with Path Signatures. - Joel Dyer; Patrick Cannon; Sebastian M. Schmon (UAI, 2024)

Collaborative Resource for Intensive care Translational science, Informatics, Comprehensive Analytics, and Learning (CRITICAL). - Yuan Luo 001; Luke V. Rasmussen; Andrew Williams 005; Jared Houghtaling; Andrew P. Michelson; Philip R. O. Payne; James J. Cimino; John D. Osborne; Prasanth Nannapaneni; Yikuan Li; Saki Amagai; Meghan Hutch; et al. (Zenodo, 2024)