| 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 |
