27 citations · 44 across the 4 of their papers we have counts for
3 papers · 1 filter
Neural Variational Gradient Descent
Lauro Langosco di Langosco, Vincent Fortuin, Heiko Strathmann
Particle-based approximate Bayesian inference approaches such as Stein Variational Gradient Descent (SVGD) combine the flexibility and convergence guarantees of sampling methods wi…
Persistent Message Passing
Heiko Strathmann, Mohammadamin Barekatain, Charles Blundell +1
Graph neural networks (GNNs) are a powerful inductive bias for modelling algorithmic reasoning procedures and data structures. Their prowess was mainly demonstrated on tasks featur…
SOM-VAE: Interpretable Discrete Representation Learning on Time Series
Vincent Fortuin, Matthias Hüser, Francesco Locatello +2
High-dimensional time series are common in many domains. Since human cognition is not optimized to work well in high-dimensional spaces, these areas could benefit from interpretabl…