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| 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 |
| Compact Bayesian Neural Networks via pruned MCMC sampling | Jan 12, 2025 | Network PruningUncertainty Quantification | 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 Inference in Multi-task Cox Process Models | May 24, 2018 | Gaussian ProcessesPoint Processes | CodeCode Available | 0 | 5 |
