| Variational Few-Shot Learning | Oct 1, 2019 | Few-Shot LearningMetric Learning | —Unverified | 0 |
| Tightening Bounds for Variational Inference by Revisiting Perturbation Theory | Sep 30, 2019 | Gaussian ProcessesStochastic Optimization | —Unverified | 0 |
| Semi-supervised voice conversion with amortized variational inference | Sep 30, 2019 | Variational InferenceVoice Conversion | —Unverified | 0 |
| On PAC-Bayes Bounds for Deep Neural Networks using the Loss Curvature | Sep 25, 2019 | Variational Inference | —Unverified | 0 |
| Meta-Learning for Variational Inference | Sep 25, 2019 | Bayesian InferenceComputational Efficiency | —Unverified | 0 |
| Gaussian Process Meta-Representations Of Neural Networks | Sep 25, 2019 | Active LearningBayesian Inference | —Unverified | 0 |
| An Information Theoretic Approach to Distributed Representation Learning | Sep 25, 2019 | Representation LearningVariational Inference | —Unverified | 0 |
| Refining the variational posterior through iterative optimization | Sep 25, 2019 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Probabilistic View of Multi-agent Reinforcement Learning: A Unified Approach | Sep 25, 2019 | Multi-agent Reinforcement Learningreinforcement-learning | —Unverified | 0 |
| Hierarchical Bayes Autoencoders | Sep 25, 2019 | DecoderVariational Inference | —Unverified | 0 |
