Variational inference and learning for continuous-time nonlinear state-space models
PAC-Bayes Analysis: Links to Luckiness and Applications
Flow-based Bayesian Estimation of Nonlinear Differential Equations for Modeling Biological Network
From kernels to causal inference
Learning Convex Inference of Marginals
Neighbourhood Components Analysis and Metric Learning
Unifying Divergence Minimization and Statistical Inference via Convex Duality
Stationary Subspace Analysis
Poster Spotlights 2
Spectral Clustering and Embedding with Hidden Markov Models