| Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification | Dec 4, 2020 | Bayesian InferenceDecision Making Under Uncertainty | CodeCode Available | 1 |
| On Variational Inference for User Modeling in Attribute-Driven Collaborative Filtering | Dec 2, 2020 | AttributeBIG-bench Machine Learning | —Unverified | 0 |
| TAN-NTM: Topic Attention Networks for Neural Topic Modeling | Dec 2, 2020 | Document ClassificationKeyphrase Generation | —Unverified | 0 |
| A Semantically Consistent and Syntactically Variational Encoder-Decoder Framework for Paraphrase Generation | Dec 1, 2020 | DecoderDiversity | —Unverified | 0 |
| Identifying signal and noise structure in neural population activity with Gaussian process factor models | Dec 1, 2020 | Variational Inference | —Unverified | 0 |
| Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks | Dec 1, 2020 | Anomaly DetectionImputation | —Unverified | 0 |
| Graph Stochastic Neural Networks for Semi-supervised Learning | Dec 1, 2020 | ClassificationGeneral Classification | CodeCode Available | 1 |
| Bidirectional Convolutional Poisson Gamma Dynamical Systems | Dec 1, 2020 | Bayesian InferenceSentence | CodeCode Available | 0 |
| Stochastic Deep Gaussian Processes over Graphs | Dec 1, 2020 | Gaussian ProcessesVariational Inference | CodeCode Available | 1 |
| Introducing Routing Uncertainty in Capsule Networks | Dec 1, 2020 | ObjectVariational Inference | —Unverified | 0 |
| Efficient Low Rank Gaussian Variational Inference for Neural Networks | Dec 1, 2020 | Variational Inference | CodeCode Available | 0 |
| Generalized Variational Continual Learning | Nov 24, 2020 | Continual LearningVariational Inference | —Unverified | 0 |
| Gradient Regularisation as Approximate Variational Inference | Nov 23, 2020 | Variational Inference | —Unverified | 0 |
| On the Inconsistency of Bayesian Inference for Misspecified Neural Networks | Nov 23, 2020 | Bayesian Inferenceregression | —Unverified | 0 |
| Rethinking Function-Space Variational Inference in Bayesian Neural Networks | Nov 23, 2020 | Variational Inference | —Unverified | 0 |
| Neural Linear Models with Functional Gaussian Process Priors | Nov 23, 2020 | Gaussian Processesregression | —Unverified | 0 |
| Variational Refinement for Importance SamplingUsing the Forward Kullback-Leibler Divergence | Nov 23, 2020 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Scalable Hybrid Hidden Markov Model with Gaussian Process Emission for Sequential Time-series Observations | Nov 23, 2020 | Time SeriesTime Series Analysis | —Unverified | 0 |
| Marginal Likelihood Gradient for Bayesian Neural Networks | Nov 23, 2020 | Variational Inference | —Unverified | 0 |
| The Gaussian Process Latent Autoregressive Model | Nov 23, 2020 | DenoisingGaussian Processes | —Unverified | 0 |
| Generative Video Compression as Hierarchical Variational Inference | Nov 23, 2020 | Density EstimationVariational Inference | —Unverified | 0 |
| Gaussian Process Latent Variable Flows for Massively Missing Data | Nov 23, 2020 | Dimensionality ReductionGaussian Processes | —Unverified | 0 |
| Gaussian Density Parametrization Flow: Particle and Stochastic Approaches | Nov 23, 2020 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Parametric Bootstrap Ensembles as Variational Inference | Nov 23, 2020 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations | Nov 21, 2020 | 4kSemi-Supervised Image Classification | CodeCode Available | 1 |
