| Towards Causal Representation Learning and Deconfounding from Indefinite Data | May 4, 2023 | Causal DiscoveryDisentanglement | —Unverified | 0 |
| Tensorizing flows: a tool for variational inference | May 3, 2023 | Tensor NetworksVariational Inference | —Unverified | 0 |
| Variational Inference for Bayesian Neural Networks under Model and Parameter Uncertainty | May 1, 2023 | Bayesian InferenceVariational Inference | CodeCode Available | 0 |
| Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach | Apr 25, 2023 | Causal InferenceDecision Making | —Unverified | 0 |
| Score-Based Diffusion Models as Principled Priors for Inverse Imaging | Apr 23, 2023 | DeblurringDenoising | CodeCode Available | 1 |
| Machine Learning and the Future of Bayesian Computation | Apr 21, 2023 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation | Apr 16, 2023 | NeRFObject | —Unverified | 0 |
| The Deep Latent Position Topic Model for Clustering and Representation of Networks with Textual Edges | Apr 14, 2023 | ClusteringModel Selection | —Unverified | 0 |
| Bayesian Inference on Brain-Computer Interfaces via GLASS | Apr 14, 2023 | Bayesian InferenceEEG | CodeCode Available | 0 |
| Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box | Apr 11, 2023 | Probabilistic ProgrammingStochastic Optimization | CodeCode Available | 0 |