| Generative locally linear embedding: A module for manifold unfolding and visualization | Jul 6, 2021 | Data VisualizationDimensionality Reduction | CodeCode Available | 1 |
| Deep Gaussian Process Emulation using Stochastic Imputation | Jul 4, 2021 | Gaussian ProcessesImputation | CodeCode Available | 1 |
| Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network | Jun 30, 2021 | Topic ModelsVariational Inference | CodeCode Available | 1 |
| Continuous-Time Deep Glioma Growth Models | Jun 23, 2021 | Time SeriesTime Series Analysis | CodeCode Available | 1 |
| Variational multiple shooting for Bayesian ODEs with Gaussian processes | Jun 21, 2021 | Bayesian InferenceGaussian Processes | CodeCode Available | 1 |
| Variational Causal Networks: Approximate Bayesian Inference over Causal Structures | Jun 14, 2021 | Bayesian InferenceCausal Inference | CodeCode Available | 1 |
| Deep Conditional Gaussian Mixture Model for Constrained Clustering | Jun 11, 2021 | ClusteringConstrained Clustering | CodeCode Available | 1 |
| Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation | Jun 11, 2021 | Graph GenerationVariational Inference | CodeCode Available | 1 |
| A Deep Variational Approach to Clustering Survival Data | Jun 10, 2021 | ClusteringDeep Clustering | CodeCode Available | 1 |
| Deep Switching State Space Model (DS^3M) for Nonlinear Time Series Forecasting with Regime Switching | Jun 4, 2021 | Time SeriesTime Series Analysis | CodeCode Available | 1 |
| A Differentiable Point Process with Its Application to Spiking Neural Networks | Jun 2, 2021 | Variational Inference | CodeCode Available | 1 |
| Non-negative matrix factorization algorithms greatly improve topic model fits | May 27, 2021 | parameter estimationTopic Models | CodeCode Available | 1 |
| DiBS: Differentiable Bayesian Structure Learning | May 25, 2021 | Causal DiscoveryVariational Inference | CodeCode Available | 1 |
| What Are Bayesian Neural Network Posteriors Really Like? | Apr 29, 2021 | Data AugmentationVariational Inference | CodeCode Available | 1 |
| Learning by example: fast reliability-aware seismic imaging with normalizing flows | Apr 13, 2021 | Bayesian InferenceSeismic Imaging | CodeCode Available | 1 |
| Generative Locally Linear Embedding | Apr 4, 2021 | Dimensionality ReductionVariational Inference | CodeCode Available | 1 |
| Storchastic: A Framework for General Stochastic Automatic Differentiation | Apr 1, 2021 | Variational Inference | CodeCode Available | 1 |
| D3p -- A Python Package for Differentially-Private Probabilistic Programming | Mar 22, 2021 | Bayesian InferenceProbabilistic Programming | CodeCode Available | 1 |
| A practical tutorial on Variational Bayes | Mar 1, 2021 | Bayesian InferenceVariational Inference | CodeCode Available | 1 |
| Deep Stochastic Volatility Model | Feb 25, 2021 | modelVariational Inference | CodeCode Available | 1 |
| Differentiable Particle Filtering via Entropy-Regularized Optimal Transport | Feb 15, 2021 | State Space ModelsVariational Inference | CodeCode Available | 1 |
| Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations | Feb 12, 2021 | Variational Inference | CodeCode Available | 1 |
| Variational Inference for Deblending Crowded Starfields | Feb 4, 2021 | Bayesian InferenceVariational Inference | CodeCode Available | 1 |
| Deep Deterministic Information Bottleneck with Matrix-based Entropy Functional | Jan 31, 2021 | Variational Inference | CodeCode Available | 1 |
| Preconditioned training of normalizing flows for variational inference in inverse problems | Jan 11, 2021 | compressed sensingVariational Inference | CodeCode Available | 1 |
