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Found 6 papers, 2 papers with code
Learning Robust Dynamics through Variational Sparse Gating
Learning world models from their sensory inputs enables agents to plan for actions by imagining their future outcomes.
Dynamic Inference with Neural Interpreters
Modern neural network architectures can leverage large amounts of data to generalize well within the training distribution.
Function Contrastive Learning of Transferable Meta-Representations
This \emph{meta-representation}, which is computed from a few observed examples of the underlying function, is learned jointly with the predictive model.
Function Contrastive Learning of Transferable Representations
Few-shot-learning seeks to find models that are capable of fast-adaptation to novel tasks which are not encountered during training.
TriFinger: An Open-Source Robot for Learning Dexterity
Dexterous object manipulation remains an open problem in robotics, despite the rapid progress in machine learning during the past decade.
Explanations for Temporal Recommendations
Recommendation systems are an integral part of Artificial Intelligence (AI) and have become increasingly important in the growing age of commercialization in AI.
