3 papers
stat.AP2026
WaST: a formalisation of the Wave model with associated statistical inference and applications
Grégoire Clarté
We propose a mathematical formalisation of the ``wave model'' originally developed in historical linguistics but with further applications in human sciences. This model assumes new…
stat.ML2023
Practical Equivariances via Relational Conditional Neural Processes
Daolang Huang, Manuel Haussmann, Ulpu Remes +5
Conditional Neural Processes (CNPs) are a class of metalearning models popular for combining the runtime efficiency of amortized inference with reliable uncertainty quantification.…
stat.ML2023
Fast post-process Bayesian inference with Variational Sparse Bayesian Quadrature
Chengkun Li, Grégoire Clarté, Martin Jørgensen +1
In applied Bayesian inference scenarios, users may have access to a large number of pre-existing model evaluations, for example from maximum-a-posteriori (MAP) optimization runs. H…