4 citations · 5 across the 2 of their papers we have counts for
5 papers
Automatic structured variational inference
Luca Ambrogioni, Kate Lin, Emily Fertig +4
Stochastic variational inference offers an attractive option as a default method for differentiable probabilistic programming. However, the performance of the variational approach…
The Indian Chefs Process
Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier +6
This paper introduces the Indian Chefs Process (ICP), a Bayesian nonparametric prior on the joint space of infinite directed acyclic graphs (DAGs) and orders that generalizes India…
Wasserstein Variational Inference
Luca Ambrogioni, Umut Güçlü, Yağmur Güçlütürk +3
This paper introduces Wasserstein variational inference, a new form of approximate Bayesian inference based on optimal transport theory. Wasserstein variational inference uses a ne…
Forward Amortized Inference for Likelihood-Free Variational Marginalization
Luca Ambrogioni, Umut Güçlü, Julia Berezutskaya +5
In this paper, we introduce a new form of amortized variational inference by using the forward KL divergence in a joint-contrastive variational loss. The resulting forward amortize…
GP CaKe: Effective brain connectivity with causal kernels
Luca Ambrogioni, Max Hinne, Marcel van Gerven +1
A fundamental goal in network neuroscience is to understand how activity in one region drives activity elsewhere, a process referred to as effective connectivity. Here we propose t…