Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics von Schmon, Sebastian M., Gagnon, Philippe

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Black-box Bayesian inference for agent-based models von Dyer, Joel, Cannon, Patrick, Farmer, J. Doyne, Schmon, Sebastian M.

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Optimal scaling of random-walk Metropolis algorithms using Bayesian large-sample asymptotics von Schmon, Sebastian M, Gagnon, Philippe

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Investigating the Impact of Model Misspecification in Neural Simulation-based Inference von Cannon, Patrick, Ward, Daniel, Schmon, Sebastian M

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Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation von Dyer, Joel, Cannon, Patrick, Schmon, Sebastian M

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Approximate Bayesian Computation with Path Signatures von Dyer, Joel, Cannon, Patrick, Schmon, Sebastian M

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High Performance Simulation for Scalable Multi-Agent Reinforcement Learning von Langham-Lopez, Jordan, Schmon, Sebastian M, Cannon, Patrick

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Calibrating Agent-based Models to Microdata with Graph Neural Networks von Dyer, Joel, Cannon, Patrick, Farmer, J. Doyne, Schmon, Sebastian M

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A General Framework for Survival Analysis and Multi-State Modelling von Groha, Stefan, Schmon, Sebastian M, Gusev, Alexander

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PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis von Wu, Yan, Wershof, Esther, Schmon, Sebastian M, Nassar, Marcel, Osiński, Błażej, Eksi, Ridvan, Zhang, Kun, Graepel, Thore

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Optimal scaling of random-walk Metropolis algorithms using Bayesian large-sample asymptotics von Schmon, Sebastian M, Gagnon, Philippe

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Robust Neural Posterior Estimation and Statistical Model Criticism von Ward, Daniel, Cannon, Patrick, Beaumont, Mark, Fasiolo, Matteo, Schmon, Sebastian M

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Generalized Posteriors in Approximate Bayesian Computation von Schmon, Sebastian M, Cannon, Patrick W, Knoblauch, Jeremias

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Generalized Posteriors in Approximate Bayesian Computation von Schmon, Sebastian M, Cannon, Patrick W, Knoblauch, Jeremias

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Bernoulli Race Particle Filters von Schmon, Sebastian M, Doucet, Arnaud, Deligiannidis, George

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Approximate Bayesian Computation with Path Signatures von Dyer, Joel, Cannon, Patrick, Schmon, Sebastian M

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Investigating the Impact of Model Misspecification in Neural Simulation-based Inference von Cannon, Patrick, Ward, Daniel, Schmon, Sebastian M

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Implicit Priors for Knowledge Sharing in Bayesian Neural Networks von Fitzsimons, Jack K, Schmon, Sebastian M, Roberts, Stephen J

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Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation von Dyer, Joel, Cannon, Patrick, Schmon, Sebastian M

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Learning Multimodal VAEs through Mutual Supervision von Joy, Tom, Shi, Yuge, Torr, Philip H. S, Rainforth, Tom, Schmon, Sebastian M, Siddharth, N

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