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What's in it for me? Augmenting Recommended Learning Resources with Navigable Annotations
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Disentangled Skill Embeddings for Reinforcement Learning
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High-Dimensional Bayesian Optimization Using Low-Dimensional Feature Spaces
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On the Gromov-Wasserstein distance and Coupled Deep Generative Models
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Variational Integrator Networks
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Fast Decomposable Submodular Function Minimization using Constrained Total Variation
We consider the problem of minimizing the sum of submodular set functions assuming minimization oracles of each summand function. Most …
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Deep Gaussian Processes with Importance-Weighted Variational Inference
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Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets
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Towards an Integrative Educational Recommender for Lifelong Learners
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Variational Integrator Networks for Physically Meaningful Embeddings
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