| Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural Networks | Nov 4, 2023 | Active LearningDecision Making | CodeCode Available | 0 | 5 |
| Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte Carlo | Oct 25, 2021 | Image RegistrationUncertainty Quantification | CodeCode Available | 0 | 5 |
| Unconstrained Monotonic Neural Networks | Aug 14, 2019 | Density EstimationVariational Inference | CodeCode Available | 0 | 5 |
| Understanding MCMC Dynamics as Flows on the Wasserstein Space | Feb 1, 2019 | Novel ConceptsVariational Inference | CodeCode Available | 0 | 5 |
| GFlowNets and variational inference | Oct 2, 2022 | DiversityReinforcement Learning (RL) | CodeCode Available | 0 | 5 |
| Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning | May 12, 2022 | Gaussian ProcessesUncertainty Quantification | CodeCode Available | 0 | 5 |
| Hamiltonian Variational Auto-Encoder | May 29, 2018 | Variational Inference | CodeCode Available | 0 | 5 |
| Generating Neural Networks with Neural Networks | Jan 6, 2018 | DiversityVariational Inference | CodeCode Available | 0 | 5 |
| Generative Adversarial Networks with Decoder-Encoder Output Noise | Jul 11, 2018 | DecoderImage Generation | 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 |
