| Entity Abstraction in Visual Model-Based Reinforcement Learning | Oct 28, 2019 | modelModel-based Reinforcement Learning | CodeCode Available | 0 |
| Implicit Posterior Variational Inference for Deep Gaussian Processes | Oct 26, 2019 | Gaussian ProcessesVariational Inference | CodeCode Available | 0 |
| Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework | Oct 26, 2019 | Knowledge DistillationVariational Inference | —Unverified | 0 |
| Stabilising priors for robust Bayesian deep learning | Oct 23, 2019 | Deep LearningVariational Inference | —Unverified | 0 |
| Sparse Orthogonal Variational Inference for Gaussian Processes | Oct 23, 2019 | Gaussian ProcessesMulti-class Classification | CodeCode Available | 1 |
| Unifying Variational Inference and PAC-Bayes for Supervised Learning that Scales | Oct 23, 2019 | MuJoCoVariational Inference | CodeCode Available | 0 |
| Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems | Oct 21, 2019 | Time SeriesTime Series Analysis | —Unverified | 0 |
| Single Episode Policy Transfer in Reinforcement Learning | Oct 17, 2019 | reinforcement-learningReinforcement Learning | CodeCode Available | 0 |
| Rapid Model Comparison by Amortizing Across Models | Oct 16, 2019 | modelTopic Models | CodeCode Available | 0 |
| Deep Amortized Variational Inference for Multivariate Time Series Imputation with Latent Gaussian Process Models | Oct 16, 2019 | Deep LearningDimensionality Reduction | —Unverified | 0 |
| Distributional Bayesian optimisation for variational inference on black-box simulators | Oct 16, 2019 | Bayesian OptimisationVariational Inference | CodeCode Available | 0 |
| Structured Semi-Implicit Variational Inference | Oct 16, 2019 | Variational Inference | —Unverified | 0 |
| Challenges in Computing and Optimizing Upper Bounds of Marginal Likelihood based on Chi-Square Divergences | Oct 16, 2019 | DiagnosticVariational Inference | —Unverified | 0 |
| Pseudo-Bayesian Learning via Direct Loss Minimization with Applications to Sparse Gaussian Process Models | Oct 16, 2019 | Variational Inference | —Unverified | 0 |
| Scalable Gradients and Variational Inference for Stochastic Differential Equations | Oct 16, 2019 | Time SeriesTime Series Analysis | —Unverified | 0 |
| Optimal Transport for Distribution Adaptation in Bayesian Hilbert Maps | Oct 16, 2019 | Variational Inference | —Unverified | 0 |
| Stein Variational Gradient Descent for Approximate Bayesian Computation | Oct 16, 2019 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Newtonian Monte Carlo: a second-order gradient method for speeding up MCMC | Oct 16, 2019 | Variational Inference | —Unverified | 0 |
| Global Approximate Inference via Local Linearisation for Temporal Gaussian Processes | Oct 16, 2019 | Bayesian InferenceGaussian Processes | —Unverified | 0 |
| Interpretable User Models via Decision-rule Gaussian Processes: Preliminary Results on Energy Storage | Oct 16, 2019 | Bayesian InferenceGaussian Processes | —Unverified | 0 |
| Langevin Dynamics as Nonparametric Variational Inference | Oct 16, 2019 | Variational Inference | —Unverified | 0 |
| Bijectors.jl: Flexible transformations for probability distributions | Oct 16, 2019 | Bayesian InferenceVariational Inference | CodeCode Available | 0 |
| Sequential Learning for Dirichlet Process Mixtures | Oct 16, 2019 | Variational Inference | —Unverified | 0 |
| Parametric Gaussian Process Regressors | Oct 16, 2019 | regressionVariational Inference | —Unverified | 0 |
| Regularized Sparse Gaussian Processes | Oct 13, 2019 | Facial Expression Recognition (FER)Gaussian Processes | —Unverified | 0 |
| Validated Variational Inference via Practical Posterior Error Bounds | Oct 9, 2019 | Bayesian InferenceVariational Inference | CodeCode Available | 1 |
| High Mutual Information in Representation Learning with Symmetric Variational Inference | Oct 4, 2019 | DecoderRepresentation Learning | —Unverified | 0 |
| Streamlined Variational Inference for Linear Mixed Models with Crossed Random Effects | Oct 4, 2019 | Variational Inference | —Unverified | 0 |
| Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization | Oct 4, 2019 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| The Neural Moving Average Model for Scalable Variational Inference of State Space Models | Oct 2, 2019 | Bayesian InferenceNormalising Flows | CodeCode Available | 0 |
| CWAE-IRL: Formulating a supervised approach to Inverse Reinforcement Learning problem | Oct 2, 2019 | reinforcement-learningReinforcement Learning | —Unverified | 0 |
| An Introduction to Probabilistic Spiking Neural Networks: Probabilistic Models, Learning Rules, and Applications | Oct 2, 2019 | Variational Inference | —Unverified | 0 |
| A Deep Factorization of Style and Structure in Fonts | Oct 2, 2019 | Variational Inference | CodeCode Available | 0 |
| Robust Variational Bayesian Point Set Registration | Oct 1, 2019 | Variational Inference | —Unverified | 0 |
| Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference | Oct 1, 2019 | Activity RecognitionBayesian Inference | —Unverified | 0 |
| 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 |
| Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference | Sep 30, 2019 | Bayesian InferenceVariational Inference | CodeCode Available | 1 |
| Semi-supervised voice conversion with amortized variational inference | Sep 30, 2019 | Variational InferenceVoice Conversion | —Unverified | 0 |
| Meta-Learning for Variational Inference | Sep 25, 2019 | Bayesian InferenceComputational Efficiency | —Unverified | 0 |
| Latent Variables on Spheres for Sampling and Inference | Sep 25, 2019 | Variational Inference | —Unverified | 0 |
| Gaussian Process Meta-Representations Of Neural Networks | Sep 25, 2019 | Active LearningBayesian Inference | —Unverified | 0 |
| BasisVAE: Orthogonal Latent Space for Deep Disentangled Representation | Sep 25, 2019 | DisentanglementVariational Inference | —Unverified | 0 |
| On PAC-Bayes Bounds for Deep Neural Networks using the Loss Curvature | Sep 25, 2019 | Variational Inference | —Unverified | 0 |
| On the Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks | Sep 25, 2019 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| LIA: Latently Invertible Autoencoder with Adversarial Learning | Sep 25, 2019 | DecoderGenerative Adversarial Network | —Unverified | 0 |
| An Information Theoretic Approach to Distributed Representation Learning | Sep 25, 2019 | Representation LearningVariational Inference | —Unverified | 0 |
| Benefits of Overparameterization in Single-Layer Latent Variable Generative Models | Sep 25, 2019 | Variational Inference | —Unverified | 0 |
| Shallow VAEs with RealNVP Prior Can Perform as Well as Deep Hierarchical VAEs | Sep 25, 2019 | Variational Inference | —Unverified | 0 |
| Refining the variational posterior through iterative optimization | Sep 25, 2019 | Bayesian InferenceVariational Inference | —Unverified | 0 |
