
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures
Learning the causal structure that underlies data is a crucial step towa...
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MetaLearning Reliable Priors in the Function Space
MetaLearning promises to enable more dataefficient inference by harnes...
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DiBS: Differentiable Bayesian Structure Learning
Bayesian structure learning allows inferring Bayesian network structure ...
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Robustness to Pruning Predicts Generalization in Deep Neural Networks
Existing generalization measures that aim to capture a model's simplicit...
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PACOH: BayesOptimal MetaLearning with PACGuarantees
Metalearning can successfully acquire useful inductive biases from data...
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Noise Regularization for Conditional Density Estimation
Modelling statistical relationships beyond the conditional mean is cruci...
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Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks
Given a set of empirical observations, conditional density estimation ai...
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ProMP: Proximal MetaPolicy Search
Credit assignment in Metareinforcement learning (MetaRL) is still poor...
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ModelBased Reinforcement Learning via MetaPolicy Optimization
Modelbased reinforcement learning approaches carry the promise of being...
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Introducing the Simulated Flying Shapes and Simulated Planar Manipulator Datasets
We release two artificial datasets, Simulated Flying Shapes and Simulate...
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Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution
We present a novel deep neural network architecture for representing rob...
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Jonas Rothfuss
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