| Adversarial Purification with the Manifold Hypothesis | Oct 26, 2022 | Adversarial PurificationAdversarial Robustness | —Unverified | 0 |
| Disentangled Representation Learning with Transmitted Information Bottleneck | Nov 3, 2023 | DisentanglementRepresentation Learning | —Unverified | 0 |
| A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods | May 24, 2023 | Deep LearningUncertainty Quantification | —Unverified | 0 |
| Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics | Jan 1, 2020 | Variational Inference | —Unverified | 0 |
| Discrete-Valued Neural Networks Using Variational Inference | Jan 1, 2018 | QuantizationVariational Inference | —Unverified | 0 |
| Disentangled Skill Embeddings for Reinforcement Learning | Jun 21, 2019 | Hierarchical Reinforcement Learningreinforcement-learning | —Unverified | 0 |
| AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms | May 19, 2017 | Variational Inference | —Unverified | 0 |
| A recursive Bayesian neural network for constitutive modeling of sands under monotonic loading | Jan 17, 2025 | Bayesian InferenceSand | —Unverified | 0 |
| Discrete flow posteriors for variational inference in discrete dynamical systems | May 28, 2018 | GPUVariational Inference | —Unverified | 0 |
| Black-Box Autoregressive Density Estimation for State-Space Models | Nov 20, 2018 | Bayesian InferenceDeep Learning | —Unverified | 0 |
