| Learning to infer in recurrent biological networks | Jun 18, 2020 | Bayesian InferenceVariational Inference | CodeCode Available | 0 |
| Constraining Variational Inference with Geometric Jensen-Shannon Divergence | Jun 18, 2020 | Variational Inference | CodeCode Available | 1 |
| Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization | Jun 18, 2020 | Variational InferenceVariational Monte Carlo | —Unverified | 0 |
| Categorical Normalizing Flows via Continuous Transformations | Jun 17, 2020 | DecoderInductive Bias | CodeCode Available | 1 |
| Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF | Jun 17, 2020 | Bayesian InferenceState Space Models | —Unverified | 0 |
| Analytical Probability Distributions and EM-Learning for Deep Generative Networks | Jun 17, 2020 | Anomaly DetectionImputation | —Unverified | 0 |
| Density Deconvolution with Normalizing Flows | Jun 16, 2020 | Density EstimationVariational Inference | CodeCode Available | 1 |
| PAC-Bayesian Generalization Bounds for MultiLayer Perceptrons | Jun 16, 2020 | Generalization BoundsVariational Inference | —Unverified | 0 |
| A Deterministic Approximation to Neural SDEs | Jun 16, 2020 | Time Series AnalysisUncertainty Quantification | —Unverified | 0 |
| Manifold GPLVMs for discovering non-Euclidean latent structure in neural data | Jun 12, 2020 | Variational Inference | CodeCode Available | 1 |
| Approximate Inference for Spectral Mixture Kernel | Jun 12, 2020 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Learning to Learn Kernels with Variational Random Features | Jun 11, 2020 | Few-Shot LearningMeta-Learning | CodeCode Available | 0 |
| Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks | Jun 11, 2020 | Variational Inference | —Unverified | 0 |
| Deep Structural Causal Models for Tractable Counterfactual Inference | Jun 11, 2020 | counterfactualCounterfactual Inference | CodeCode Available | 1 |
| Recurrent Flow Networks: A Recurrent Latent Variable Model for Density Modelling of Urban Mobility | Jun 9, 2020 | Variational Inference | CodeCode Available | 0 |
| Structured Variational Inference in Partially Observable Unstable Gaussian Process State Space Models | Jun 8, 2020 | State Space ModelsVariational Inference | —Unverified | 0 |
| Improving Inference for Neural Image Compression | Jun 7, 2020 | Image CompressionVariational Inference | CodeCode Available | 1 |
| Bayesian Neural Network via Stochastic Gradient Descent | Jun 4, 2020 | regressionVariational Inference | —Unverified | 0 |
| Quadruply Stochastic Gaussian Processes | Jun 4, 2020 | Gaussian Processesregression | CodeCode Available | 1 |
| A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning | Jun 3, 2020 | Representation LearningSelf-Supervised Learning | —Unverified | 0 |
| Variational Inference and Learning of Piecewise-linear Dynamical Systems | Jun 2, 2020 | Head Pose EstimationModel Selection | —Unverified | 0 |
| From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models | Jun 1, 2020 | Variational Inference | —Unverified | 0 |
| VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics | May 27, 2020 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Longitudinal Deep Kernel Gaussian Process Regression | May 24, 2020 | Gaussian Processesregression | —Unverified | 0 |
| Functional Space Variational Inference for Uncertainty Estimation in Computer Aided Diagnosis | May 24, 2020 | Bayesian InferenceLesion Classification | —Unverified | 0 |
