193 citations · 201 across the 3 of their papers we have counts for
4 papers
AlignNet: Unsupervised Entity Alignment
Antonia Creswell, Kyriacos Nikiforou, Oriol Vinyals +8
Recently developed deep learning models are able to learn to segment scenes into component objects without supervision. This opens many new and exciting avenues of research, allowi…
Multi-Object Representation Learning with Iterative Variational Inference
Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra +6
Human perception is structured around objects which form the basis for our higher-level cognition and impressive systematic generalization abilities. Yet most work on representatio…
MONet: Unsupervised Scene Decomposition and Representation
Christopher P. Burgess, Loic Matthey, Nicholas Watters +4
The ability to decompose scenes in terms of abstract building blocks is crucial for general intelligence. Where those basic building blocks share meaningful properties, interaction…
An investigation of model-free planning
Arthur Guez, Mehdi Mirza, Karol Gregor +10
The field of reinforcement learning (RL) is facing increasingly challenging domains with combinatorial complexity. For an RL agent to address these challenges, it is essential that…