Search Results for author: Tim Rocktaschel

Found 3 papers, 2 papers with code

Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning

1 code implementation8 Feb 2021 Zhengyao Jiang, Pasquale Minervini, Minqi Jiang, Tim Rocktaschel

In this work, we show that we can incorporate relational inductive biases, encoded in the form of relational graphs, into agents.

reinforcement-learning reinforcement Learning

Generating Interactive Worlds with Text

no code implementations20 Nov 2019 Angela Fan, Jack Urbanek, Pratik Ringshia, Emily Dinan, Emma Qian, Siddharth Karamcheti, Shrimai Prabhumoye, Douwe Kiela, Tim Rocktaschel, Arthur Szlam, Jason Weston

We show that the game environments created with our approach are cohesive, diverse, and preferred by human evaluators compared to other machine learning based world construction algorithms.

BIG-bench Machine Learning Common Sense Reasoning

Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings

1 code implementation12 Jun 2019 Alexander I. Cowen-Rivers, Pasquale Minervini, Tim Rocktaschel, Matko Bosnjak, Sebastian Riedel, Jun Wang

Recent advances in Neural Variational Inference allowed for a renaissance in latent variable models in a variety of domains involving high-dimensional data.

Knowledge Graph Embeddings Knowledge Graphs +2

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