| Deep Generative Modeling for Identification of Noisy, Non-Stationary Dynamical Systems | Oct 2, 2024 | Uncertainty QuantificationVariational Inference | CodeCode Available | 0 |
| Pathwise Derivatives Beyond the Reparameterization Trick | Jun 5, 2018 | regressionVariational Inference | CodeCode Available | 0 |
| Z-Forcing: Training Stochastic Recurrent Networks | Nov 15, 2017 | Language ModelingLanguage Modelling | CodeCode Available | 0 |
| Gradient-based optimization for variational empirical Bayes multiple regression | Nov 21, 2024 | regressionVariational Inference | CodeCode Available | 0 |
| Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors | Jul 9, 2021 | Objectobject-detection | CodeCode Available | 0 |
| Deep Gaussian Processes with Importance-Weighted Variational Inference | May 14, 2019 | Gaussian ProcessesVariational Inference | CodeCode Available | 0 |
| Deep Gaussian Processes for Multi-fidelity Modeling | Mar 18, 2019 | Bayesian OptimizationDecision Making | CodeCode Available | 0 |
| Deep Gaussian Processes for Air Quality Inference | Nov 18, 2022 | Air Quality InferenceGaussian Processes | CodeCode Available | 0 |
| Learning to infer in recurrent biological networks | Jun 18, 2020 | Bayesian InferenceVariational Inference | CodeCode Available | 0 |
| Variational Latent Branching Model for Off-Policy Evaluation | Jan 28, 2023 | modelOff-policy evaluation | CodeCode Available | 0 |
| Unbiased Implicit Variational Inference | Aug 6, 2018 | regressionVariational Inference | CodeCode Available | 0 |
| GraphBTM: Graph Enhanced Autoencoded Variational Inference for Biterm Topic Model | Oct 1, 2018 | Recommendation SystemsTopic Models | CodeCode Available | 0 |
| Graphite: Iterative Generative Modeling of Graphs | Mar 28, 2018 | Density EstimationGeneral Classification | CodeCode Available | 0 |
| Uncertainty-Aware Attention for Reliable Interpretation and Prediction | May 24, 2018 | PredictionVariational Inference | CodeCode Available | 0 |
| Deep Gaussian Markov Random Fields | Feb 18, 2020 | Variational Inference | CodeCode Available | 0 |
| Advancing calibration for stochastic agent-based models in epidemiology with Stein variational inference and Gaussian process surrogates | Feb 26, 2025 | EpidemiologyVariational Inference | CodeCode Available | 0 |
| Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix | Oct 14, 2024 | Bayesian InferenceVariational Inference | CodeCode Available | 0 |
| Uncertainty-based Continual Learning with Adaptive Regularization | May 28, 2019 | Continual LearningReinforcement Learning | CodeCode Available | 0 |
| Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility | Jul 11, 2022 | Face RecognitionFairness | CodeCode Available | 0 |
| A Theoretically Grounded Application of Dropout in Recurrent Neural Networks | Dec 16, 2015 | Bayesian InferenceDeep Learning | CodeCode Available | 0 |
| Stable Training of Normalizing Flows for High-dimensional Variational Inference | Feb 26, 2024 | Variational Inference | CodeCode Available | 0 |
| Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors | Jun 22, 2020 | Bayesian Inferenceregression | CodeCode Available | 0 |
| Hamiltonian Variational Auto-Encoder | May 29, 2018 | Variational Inference | CodeCode Available | 0 |
| Handling the Positive-Definite Constraint in the Bayesian Learning Rule | Feb 24, 2020 | validVariational Inference | CodeCode Available | 0 |
| Harnessing Out-Of-Distribution Examples via Augmenting Content and Style | Jul 7, 2022 | Data AugmentationDisentanglement | CodeCode Available | 0 |
