20 citations · 31 across the 4 of their papers we have counts for
3 papers · 1 filter
Prequential MDL for Causal Structure Learning with Neural Networks
Jorg Bornschein, Silvia Chiappa, Alan Malek +1
Learning the structure of Bayesian networks and causal relationships from observations is a common goal in several areas of science and technology. We show that the prequential min…
Small Data, Big Decisions: Model Selection in the Small-Data Regime
Jorg Bornschein, Francesco Visin, Simon Osindero
Highly overparametrized neural networks can display curiously strong generalization performance - a phenomenon that has recently garnered a wealth of theoretical and empirical rese…
Variational Memory Addressing in Generative Models
Jörg Bornschein, Andriy Mnih, Daniel Zoran +1
Aiming to augment generative models with external memory, we interpret the output of a memory module with stochastic addressing as a conditional mixture distribution, where a read…