30 citations · 91 across the 16 of their papers we have counts for
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cs.LG2021★ 3 cited
Learning Multimodal VAEs through Mutual Supervision
Tom Joy, Yuge Shi, Philip H. S. Torr +3
Multimodal VAEs seek to model the joint distribution over heterogeneous data (e.g.\ vision, language), whilst also capturing a shared representation across such modalities. Prior w…
stat.ME2021★ 2 cited
Approximate Bayesian Computation with Path Signatures
Joel Dyer, Patrick Cannon, Sebastian M Schmon
Simulation models often lack tractable likelihood functions, making likelihood-free inference methods indispensable. Approximate Bayesian computation generates likelihood-free post…
stat.ME2021
Optimal scaling of random-walk Metropolis algorithms using Bayesian large-sample asymptotics
Sebastian M Schmon, Philippe Gagnon
High-dimensional limit theorems have been shown useful to derive tuning rules for finding the optimal scaling in random-walk Metropolis algorithms. The assumptions under which weak…