18.2k citations · 31.4k across the 96 of their papers we have counts for
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Automatic Embedding of Stories Into Collections of Independent Media
Dylan R. Ashley, Vincent Herrmann, Zachary Friggstad +2
We look at how machine learning techniques that derive properties of items in a collection of independent media can be used to automatically embed stories into such collections. To…
The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization
Róbert Csordás, Kazuki Irie, Jürgen Schmidhuber
Despite progress across a broad range of applications, Transformers have limited success in systematic generalization. The situation is especially frustrating in the case of algori…
The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers
Róbert Csordás, Kazuki Irie, Jürgen Schmidhuber
Recently, many datasets have been proposed to test the systematic generalization ability of neural networks. The companion baseline Transformers, typically trained with default hyp…
Bayesian brains and the Rényi divergence
Noor Sajid, Francesco Faccio, Lancelot Da Costa +3
Under the Bayesian brain hypothesis, behavioural variations can be attributed to different priors over generative model parameters. This provides a formal explanation for why indiv…
Reward-Weighted Regression Converges to a Global Optimum
Miroslav Štrupl, Francesco Faccio, Dylan R. Ashley +2
Reward-Weighted Regression (RWR) belongs to a family of widely known iterative Reinforcement Learning algorithms based on the Expectation-Maximization framework. In this family, le…
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling
Đorđe Miladinović, Aleksandar Stanić, Stefan Bauer +2
How to improve generative modeling by better exploiting spatial regularities and coherence in images? We introduce a novel neural network for building image generators (decoders) a…