| 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 | 5 |
| GFlowNet-EM for learning compositional latent variable models | Feb 13, 2023 | Variational Inference | CodeCode Available | 1 | 5 |
| Bayesian neural networks via MCMC: a Python-based tutorial | Apr 2, 2023 | Bayesian InferenceDeep Learning | CodeCode Available | 1 | 5 |
| Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-Supervised Segmentation | Aug 8, 2022 | Image SegmentationMedical Image Segmentation | CodeCode Available | 1 | 5 |
| Differentially Private Variational Inference for Non-conjugate Models | Oct 27, 2016 | Bayesian InferenceVariational Inference | CodeCode Available | 1 | 5 |
| Hierarchical Phrase-based Sequence-to-Sequence Learning | Nov 15, 2022 | Inductive BiasMachine Translation | CodeCode Available | 1 | 5 |
| Improving Inference for Neural Image Compression | Jun 7, 2020 | Image CompressionVariational Inference | CodeCode Available | 1 | 5 |
| Improving Variational Inference with Inverse Autoregressive Flow | Jun 15, 2016 | Variational Inference | CodeCode Available | 1 | 5 |
| A Deep Variational Approach to Clustering Survival Data | Jun 10, 2021 | ClusteringDeep Clustering | CodeCode Available | 1 | 5 |
| Interactive Segmentation as Gaussian Process Classification | Feb 28, 2023 | Binary ClassificationClassification | CodeCode Available | 1 | 5 |
| Bayesian sparsification for deep neural networks with Bayesian model reduction | Sep 21, 2023 | Deep LearningVariational Inference | CodeCode Available | 1 | 5 |
| Learn from Unpaired Data for Image Restoration: A Variational Bayes Approach | Apr 21, 2022 | DenoisingImage Denoising | CodeCode Available | 1 | 5 |
| Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series | Oct 8, 2024 | Computational EfficiencyIrregular Time Series | CodeCode Available | 1 | 5 |
| Amortized Inference for Causal Structure Learning | May 25, 2022 | Causal DiscoveryInductive Bias | CodeCode Available | 1 | 5 |
| Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees | Nov 2, 2021 | Bayesian InferenceGaussian Processes | CodeCode Available | 1 | 5 |
| BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery | Dec 6, 2021 | Causal DiscoveryStochastic Optimization | CodeCode Available | 1 | 5 |
| A Differentiable Point Process with Its Application to Spiking Neural Networks | Jun 2, 2021 | Variational Inference | CodeCode Available | 1 | 5 |
| Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs | Dec 16, 2023 | Time SeriesVariational Inference | CodeCode Available | 1 | 5 |
| Discretely Relaxing Continuous Variables for tractable Variational Inference | Sep 12, 2018 | Variational Inference | CodeCode Available | 1 | 5 |
| Deep Causal Reasoning for Recommendations | Jan 6, 2022 | Recommendation SystemsVariational Inference | CodeCode Available | 1 | 5 |
| Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling | Jun 11, 2024 | Decision MakingVariational Inference | CodeCode Available | 1 | 5 |
| Beyond Opinion Mining: Summarizing Opinions of Customer Reviews | Jun 3, 2022 | Opinion MiningOpinion Summarization | CodeCode Available | 1 | 5 |
| Bit Allocation using Optimization | Sep 20, 2022 | Variational InferenceVideo Compression | CodeCode Available | 1 | 5 |
| LINFA: a Python library for variational inference with normalizing flow and annealing | Jul 10, 2023 | Variational Inference | CodeCode Available | 1 | 5 |
| Low-rank extended Kalman filtering for online learning of neural networks from streaming data | May 31, 2023 | Bayesian InferenceVariational Inference | CodeCode Available | 1 | 5 |
| Manifold GPLVMs for discovering non-Euclidean latent structure in neural data | Jun 12, 2020 | Variational Inference | CodeCode Available | 1 | 5 |
| Counterfactual Generative Modeling with Variational Causal Inference | Oct 16, 2024 | Causal Inferencecounterfactual | CodeCode Available | 1 | 5 |
| Deep Conditional Gaussian Mixture Model for Constrained Clustering | Jun 11, 2021 | ClusteringConstrained Clustering | CodeCode Available | 1 | 5 |
| Convergence of Sparse Variational Inference in Gaussian Processes Regression | Aug 1, 2020 | Gaussian Processesregression | CodeCode Available | 1 | 5 |
| A practical tutorial on Variational Bayes | Mar 1, 2021 | Bayesian InferenceVariational Inference | CodeCode Available | 1 | 5 |
| A Probabilistic Formulation of Unsupervised Text Style Transfer | Feb 10, 2020 | DeciphermentLanguage Modelling | CodeCode Available | 1 | 5 |
| Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization | Dec 10, 2020 | Density EstimationVariational Inference | CodeCode Available | 1 | 5 |
| Deep Deterministic Information Bottleneck with Matrix-based Entropy Functional | Jan 31, 2021 | Variational Inference | CodeCode Available | 1 | 5 |
| Constraining Variational Inference with Geometric Jensen-Shannon Divergence | Jun 18, 2020 | Variational Inference | CodeCode Available | 1 | 5 |
| Adversarial Autoencoders | Nov 18, 2015 | ClusteringData Visualization | CodeCode Available | 1 | 5 |
| An Energy-Based Prior for Generative Saliency | Apr 19, 2022 | object-detectionObject Detection | CodeCode Available | 1 | 5 |
| ContraBAR: Contrastive Bayes-Adaptive Deep RL | Jun 4, 2023 | Contrastive LearningMeta Reinforcement Learning | CodeCode Available | 1 | 5 |
| An information field theory approach to Bayesian state and parameter estimation in dynamical systems | Jun 3, 2023 | parameter estimationState Estimation | CodeCode Available | 1 | 5 |
| Continual Learning via Sequential Function-Space Variational Inference | Dec 28, 2023 | Bayesian InferenceContinual Learning | CodeCode Available | 1 | 5 |
| A Probabilistic Framework for Visual Localization in Ambiguous Scenes | Jan 5, 2023 | Variational InferenceVisual Localization | CodeCode Available | 1 | 5 |
| D3p -- A Python Package for Differentially-Private Probabilistic Programming | Mar 22, 2021 | Bayesian InferenceProbabilistic Programming | CodeCode Available | 1 | 5 |
| Deep Active Inference | Oct 11, 2018 | Variational Inference | CodeCode Available | 1 | 5 |
| Understanding and Accelerating Particle-Based Variational Inference | Jul 4, 2018 | Bayesian InferenceVariational Inference | CodeCode Available | 1 | 5 |
| A theory of continuous generative flow networks | Jan 30, 2023 | Variational Inference | CodeCode Available | 1 | 5 |
| Deep Stochastic Volatility Model | Feb 25, 2021 | modelVariational Inference | CodeCode Available | 1 | 5 |
| Deep Structural Causal Models for Tractable Counterfactual Inference | Jun 11, 2020 | counterfactualCounterfactual Inference | CodeCode Available | 1 | 5 |
| Conditional Matrix Flows for Gaussian Graphical Models | Jun 12, 2023 | Model SelectionVariational Inference | CodeCode Available | 1 | 5 |
| Density Deconvolution with Normalizing Flows | Jun 16, 2020 | Density EstimationVariational Inference | CodeCode Available | 1 | 5 |
| Differentiable Causal Discovery Under Latent Interventions | Mar 4, 2022 | Causal DiscoveryVariational Inference | CodeCode Available | 1 | 5 |
| Confidence-aware Personalized Federated Learning via Variational Expectation Maximization | May 21, 2023 | Federated LearningPersonalized Federated Learning | CodeCode Available | 1 | 5 |
