| Black box variational inference for state space models | Nov 23, 2015 | State Space ModelsTime Series | CodeCode Available | 0 | 5 |
| Bridging the Gap Between Variational Inference and Wasserstein Gradient Flows | Oct 31, 2023 | Variational Inference | 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 |
| Entity Abstraction in Visual Model-Based Reinforcement Learning | Oct 28, 2019 | modelModel-based Reinforcement Learning | CodeCode Available | 0 | 5 |
| Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective Inference | Apr 17, 2024 | Variational Inference | CodeCode Available | 0 | 5 |
| Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space | Dec 5, 2023 | Variational Inference | CodeCode Available | 0 | 5 |
| Dropout Inference in Bayesian Neural Networks with Alpha-divergences | Mar 8, 2017 | Variational Inference | CodeCode Available | 0 | 5 |
| Dual Gaussian-based Variational Subspace Disentanglement for Visible-Infrared Person Re-Identification | Aug 6, 2020 | DisentanglementPerson Re-Identification | CodeCode Available | 0 | 5 |
