| Joint Mapping and Calibration via Differentiable Sensor Fusion | Nov 21, 2018 | ClusteringProbabilistic Programming | —Unverified | 0 |
| Joint Modeling of Visual Objects and Relations for Scene Graph Generation | Dec 1, 2021 | Graph EmbeddingGraph Generation | —Unverified | 0 |
| Learning Deep Latent-variable MRFs with Amortized Bethe Free Energy Minimization | Mar 27, 2019 | Variational Inference | —Unverified | 0 |
| Learning Distributions via Monte-Carlo Marginalization | Aug 11, 2023 | DecoderDensity Estimation | —Unverified | 0 |
| Learning From Unpaired Data: A Variational Bayes Approach | Sep 29, 2021 | DenoisingImage Denoising | —Unverified | 0 |
| Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? | Jul 27, 2023 | Variational Inference | —Unverified | 0 |
| A Deterministic Approximation to Neural SDEs | Jun 16, 2020 | Time Series AnalysisUncertainty Quantification | —Unverified | 0 |
| Deterministic Fokker-Planck Transport -- With Applications to Sampling, Variational Inference, Kernel Mean Embeddings & Sequential Monte Carlo | Oct 11, 2024 | Density EstimationVariational Inference | —Unverified | 0 |
| An Introduction to Probabilistic Spiking Neural Networks: Probabilistic Models, Learning Rules, and Applications | Oct 2, 2019 | Variational Inference | —Unverified | 0 |
| Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation | Oct 29, 2019 | Variational Inference | —Unverified | 0 |
