Sebastian M. Schmon

20 papers A* 3A 3Journal 13Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	A	`conf`	Approximate Bayesian Computation with Path Signatures. UAI Joel Dyer, Patrick Cannon, Sebastian M. Schmon
2024	J	`jnl`	Bayesian Computation Meets Topology. Trans. Mach. Learn. Res. Julius von Rohrscheidt, Bastian Rieck, Sebastian M. Schmon
2024	J	`jnl`	PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis. CoRR Yan Wu, Esther Wershof, Sebastian M. Schmon, Marcel Nassar, Blazej Osinski, Ridvan Eksi, Kun Zhang, Thore Graepel
2022	A	`conf`	Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation. AISTATS Joel Dyer, Patrick W. Cannon, Sebastian M. Schmon
2022	J	`jnl`	Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation. CoRR Joel Dyer, Patrick Cannon, Sebastian M. Schmon
2022	—	`conf`	AnoDDPM: Anomaly Detection with Denoising Diffusion Probabilistic Models using Simplex Noise. CVPR Workshops Julian Wyatt, Adam Leach, Sebastian M. Schmon, Chris G. Willcocks
2022	J	`jnl`	Black-box Bayesian inference for economic agent-based models. CoRR Joel Dyer, Patrick Cannon, J. Doyne Farmer, Sebastian M. Schmon
2022	J	`jnl`	Calibrating Agent-based Models to Microdata with Graph Neural Networks. CoRR Joel Dyer, Patrick Cannon, J. Doyne Farmer, Sebastian M. Schmon
2022	J	`jnl`	High Performance Simulation for Scalable Multi-Agent Reinforcement Learning. CoRR Jordan Langham-Lopez, Sebastian M. Schmon, Patrick Cannon
2022	J	`jnl`	Investigating the Impact of Model Misspecification in Neural Simulation-based Inference. CoRR Patrick Cannon, Daniel Ward, Sebastian M. Schmon
2022	A*	`conf`	Learning Multimodal VAEs through Mutual Supervision. ICLR Tom Joy, Yuge Shi, Philip H. S. Torr, Tom Rainforth, Sebastian M. Schmon, Siddharth Narayanaswamy
2022	J	`jnl`	Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics. Stat. Comput. Sebastian M. Schmon, Philippe Gagnon
2022	A*	`conf`	Robust Neural Posterior Estimation and Statistical Model Criticism. NeurIPS Daniel Ward, Patrick Cannon, Mark Beaumont, Matteo Fasiolo, Sebastian M. Schmon
2022	J	`jnl`	Robust Neural Posterior Estimation and Statistical Model Criticism. CoRR Daniel Ward, Patrick Cannon, Mark Beaumont, Matteo Fasiolo, Sebastian M. Schmon
2021	A*	`conf`	Capturing Label Characteristics in VAEs. ICLR Tom Joy, Sebastian M. Schmon, Philip H. S. Torr, Siddharth Narayanaswamy, Tom Rainforth
2021	J	`jnl`	Learning Multimodal VAEs through Mutual Supervision. CoRR Tom Joy, Yuge Shi, Philip H. S. Torr, Tom Rainforth, Sebastian M. Schmon, N. Siddharth
2020	J	`jnl`	Neural ODEs for Multi-State Survival Analysis. CoRR Stefan Groha, Sebastian M. Schmon, Alexander Gusev
2020	J	`jnl`	Rethinking Semi-Supervised Learning in VAEs. CoRR Tom Joy, Sebastian M. Schmon, Philip H. S. Torr, N. Siddharth, Tom Rainforth
2019	A	`conf`	Bernoulli Race Particle Filters. AISTATS Sebastian M. Schmon, Arnaud Doucet, George Deligiannidis
2019	J	`jnl`	Implicit Priors for Knowledge Sharing in Bayesian Neural Networks. CoRR Jack K. Fitzsimons, Sebastian M. Schmon, Stephen J. Roberts