activity
20132019
most citedTeaching Machines to Read and Comprehend

2.7k citations · 4.5k across the 19 of their papers we have counts for

collaborators

22 papers

cs.AI2019★ 49 cited

The StreetLearn Environment and Dataset

Piotr Mirowski, Andras Banki-Horvath, Keith Anderson +8

Navigation is a rich and well-grounded problem domain that drives progress in many different areas of research: perception, planning, memory, exploration, and optimisation in parti…

cs.AI2019

Learning To Follow Directions in Street View

Karl Moritz Hermann, Mateusz Malinowski, Piotr Mirowski +3

Navigating and understanding the real world remains a key challenge in machine learning and inspires a great variety of research in areas such as language grounding, planning, navi…

cs.CL2018★ 2 cited

Encoding Spatial Relations from Natural Language

Tiago Ramalho, Tomáš Kočiský, Frederic Besse +5

Natural language processing has made significant inroads into learning the semantics of words through distributional approaches, however representations learnt via these methods fa…

cs.NE2018★ 47 cited

Hyperbolic Attention Networks

Caglar Gulcehre, Misha Denil, Mateusz Malinowski +8

We introduce hyperbolic attention networks to endow neural networks with enough capacity to match the complexity of data with hierarchical and power-law structure. A few recent app…

stat.ML2018★ 12 cited

Pushing the bounds of dropout

Gábor Melis, Charles Blundell, Tomáš Kočiský +3

We show that dropout training is best understood as performing MAP estimation concurrently for a family of conditional models whose objectives are themselves lower bounded by the o…

cs.AI2018★ 31 cited

Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input

Angeliki Lazaridou, Karl Moritz Hermann, Karl Tuyls +1

The ability of algorithms to evolve or learn (compositional) communication protocols has traditionally been studied in the language evolution literature through the use of emergent…