| Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box | Apr 11, 2023 | Probabilistic ProgrammingStochastic Optimization | CodeCode Available | 0 | 5 |
| Black box variational inference for state space models | Nov 23, 2015 | State Space ModelsTime Series | CodeCode Available | 0 | 5 |
| Generative Topic Embedding: a Continuous Representation of Documents (Extended Version with Proofs) | Jun 9, 2016 | Document ClassificationVariational Inference | CodeCode Available | 0 | 5 |
| Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India | Dec 13, 2017 | BIG-bench Machine LearningVariational Inference | CodeCode Available | 0 | 5 |
| Asynchronous Temporal Fields for Action Recognition | Dec 19, 2016 | Action ClassificationAction Recognition | CodeCode Available | 0 | 5 |
| ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks | Jul 30, 2018 | Data AugmentationVariational Inference | CodeCode Available | 0 | 5 |
| Black-box Variational Inference for Stochastic Differential Equations | Feb 9, 2018 | Variational Inference | CodeCode Available | 0 | 5 |
| Jensen-Shannon Divergence Based Novel Loss Functions for Bayesian Neural Networks | Sep 23, 2022 | regressionVariational Inference | CodeCode Available | 0 | 5 |
| A Theoretically Grounded Application of Dropout in Recurrent Neural Networks | Dec 16, 2015 | Bayesian InferenceDeep Learning | CodeCode Available | 0 | 5 |
| Gradient-based optimization for variational empirical Bayes multiple regression | Nov 21, 2024 | regressionVariational Inference | CodeCode Available | 0 | 5 |
| Black Box Variational Inference | Dec 31, 2013 | Stochastic OptimizationVariational Inference | CodeCode Available | 0 | 5 |
| Classification by Re-generation: Towards Classification Based on Variational Inference | Sep 10, 2018 | ClassificationDecoder | CodeCode Available | 0 | 5 |
| Black-box Coreset Variational Inference | Nov 4, 2022 | Bayesian InferenceData Summarization | CodeCode Available | 0 | 5 |
| Amortized variational transdimensional inference | Jun 5, 2025 | Bayesian InferenceBayesian Optimization | CodeCode Available | 0 | 5 |
| End-to-End Pixel-Based Deep Active Inference for Body Perception and Action | Dec 28, 2019 | Variational Inference | CodeCode Available | 0 | 5 |
| Handling the Positive-Definite Constraint in the Bayesian Learning Rule | Feb 24, 2020 | validVariational Inference | CodeCode Available | 0 | 5 |
| Heron Inference for Bayesian Graphical Models | Feb 19, 2018 | Computational EfficiencyVariational Inference | CodeCode Available | 0 | 5 |
| Heterogeneous Multi-output Gaussian Process Prediction | May 19, 2018 | Gaussian ProcessesPrediction | CodeCode Available | 0 | 5 |
| Energy-Inspired Models: Learning with Sampler-Induced Distributions | Oct 31, 2019 | Variational Inference | CodeCode Available | 0 | 5 |
| Cognition-Mode Aware Variational Representation Learning Framework for Knowledge Tracing | Sep 3, 2023 | Knowledge TracingRepresentation Learning | CodeCode Available | 0 | 5 |
| Coherence-Aware Neural Topic Modeling | Sep 7, 2018 | Topic ModelsVariational Inference | CodeCode Available | 0 | 5 |
| Hierarchical Variational Imitation Learning of Control Programs | Dec 29, 2019 | Imitation LearningVariational Inference | CodeCode Available | 0 | 5 |
| Bijectors.jl: Flexible transformations for probability distributions | Oct 16, 2019 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
| BIISQ: Bayesian nonparametric discovery of Isoforms and Individual Specific Quantification | Mar 24, 2017 | DiversityVariational Inference | CodeCode Available | 0 | 5 |
| High Dimensional Causal Inference with Variational Backdoor Adjustment | Oct 9, 2023 | Causal InferenceVariational Inference | CodeCode Available | 0 | 5 |
| High-dimensional neural spike train analysis with generalized count linear dynamical systems | Dec 1, 2015 | Variational Inference | CodeCode Available | 0 | 5 |
| Amortised Inference in Bayesian Neural Networks | Sep 6, 2023 | Meta-LearningVariational Inference | CodeCode Available | 0 | 5 |
| Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series | Nov 4, 2021 | Data IntegrationDecoder | CodeCode Available | 0 | 5 |
| Collapsed Variational Bounds for Bayesian Neural Networks | Dec 1, 2021 | Variational Inference | CodeCode Available | 0 | 5 |
| Collapsed Variational Inference for Nonparametric Bayesian Group Factor Analysis | Sep 10, 2018 | Variational Inference | CodeCode Available | 0 | 5 |
| Bidirectional Convolutional Poisson Gamma Dynamical Systems | Dec 1, 2020 | Bayesian InferenceSentence | CodeCode Available | 0 | 5 |
| Combining Model and Parameter Uncertainty in Bayesian Neural Networks | Mar 18, 2019 | Bayesian InferenceModel Selection | CodeCode Available | 0 | 5 |
| Augment and Reduce: Stochastic Inference for Large Categorical Distributions | Jul 1, 2018 | General ClassificationRecommendation Systems | CodeCode Available | 0 | 5 |
| Community Detection in Weighted Multilayer Networks with Ambient Noise | Feb 24, 2021 | Community DetectionVariational Inference | CodeCode Available | 0 | 5 |
| A Hierarchical Bayesian Model for Deep Few-Shot Meta Learning | Jun 16, 2023 | Bayesian InferenceMeta-Learning | CodeCode Available | 0 | 5 |
| Augment and Reduce: Stochastic Inference for Large Categorical Distributions | Feb 12, 2018 | General ClassificationRecommendation Systems | CodeCode Available | 0 | 5 |
| A Compact Representation for Bayesian Neural Networks By Removing Permutation Symmetry | Dec 31, 2023 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
| Complementing Representation Deficiency in Few-shot Image Classification: A Meta-Learning Approach | Jul 21, 2020 | Few-Shot Image ClassificationFew-Shot Learning | CodeCode Available | 0 | 5 |
| A probabilistic, data-driven closure model for RANS simulations with aleatoric, model uncertainty | Jul 5, 2023 | modelVariational Inference | CodeCode Available | 0 | 5 |
| Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee | Nov 15, 2020 | Deep LearningUncertainty Quantification | CodeCode Available | 0 | 5 |
| Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features | Jun 10, 2021 | Bayesian InferenceGaussian Processes | CodeCode Available | 0 | 5 |
| Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features | Dec 1, 2021 | Bayesian InferenceGaussian Processes | CodeCode Available | 0 | 5 |
| Indian Buffet process for model selection in convolved multiple-output Gaussian processes | Mar 22, 2015 | Gaussian ProcessesModel Selection | CodeCode Available | 0 | 5 |
| Compositional uncertainty in deep Gaussian processes | Sep 17, 2019 | Bayesian InferenceGaussian Processes | CodeCode Available | 0 | 5 |
| Compound Probabilistic Context-Free Grammars for Grammar Induction | Jun 24, 2019 | Constituency Grammar InductionSentence | CodeCode Available | 0 | 5 |
| Adaptive RKHS Fourier Features for Compositional Gaussian Process Models | Jul 1, 2024 | Gaussian ProcessesVariational Inference | CodeCode Available | 0 | 5 |
| Autoencoding Pixies: Amortised Variational Inference with Graph Convolutions for Functional Distributional Semantics | May 6, 2020 | Language ModelingLanguage Modelling | CodeCode Available | 0 | 5 |
| Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning | Oct 1, 2021 | Gaussian ProcessesVariational Inference | CodeCode Available | 0 | 5 |
| Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling | Oct 12, 2021 | modelVariational Inference | CodeCode Available | 0 | 5 |
| Enhanced Variational Inference with Dyadic Transformation | Jan 30, 2019 | Variational Inference | CodeCode Available | 0 | 5 |
