| Learning Generalizable Latent Representations for Novel Degradations in Super Resolution | Jul 25, 2022 | Blind Super-ResolutionImage Super-Resolution | —Unverified | 0 | 0 |
| Learning Hard Alignments with Variational Inference | May 16, 2017 | Hard AttentionImage Captioning | —Unverified | 0 | 0 |
| Learning Invariances using the Marginal Likelihood | Aug 16, 2018 | Data AugmentationGaussian Processes | —Unverified | 0 | 0 |
| Learning in Variational Autoencoders with Kullback-Leibler and Renyi Integral Bounds | Jul 5, 2018 | DecoderVariational Inference | —Unverified | 0 | 0 |
| Learning Model Reparametrizations: Implicit Variational Inference by Fitting MCMC distributions | Aug 4, 2017 | Variational Inference | —Unverified | 0 | 0 |
| Learning noisy-OR Bayesian Networks with Max-Product Belief Propagation | Jan 31, 2023 | Variational Inference | —Unverified | 0 | 0 |
| Learning Optimal Filters Using Variational Inference | Jun 26, 2024 | Variational Inference | —Unverified | 0 | 0 |
| Learning proposals for sequential importance samplers using reinforced variational inference | Mar 16, 2019 | reinforcement-learningReinforcement Learning | —Unverified | 0 | 0 |
| Learning Robot Skills with Temporal Variational Inference | Jun 29, 2020 | Variational Inference | —Unverified | 0 | 0 |
| Learning Set Functions with Implicit Differentiation | Dec 15, 2024 | Anomaly DetectionProduct Recommendation | —Unverified | 0 | 0 |
| Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels | Dec 1, 2015 | DenoisingGaussian Processes | —Unverified | 0 | 0 |
| Learning Supervised Topic Models for Classification and Regression from Crowds | Aug 17, 2018 | ClassificationGeneral Classification | —Unverified | 0 | 0 |
| Learning the joint distribution of two sequences using little or no paired data | Dec 6, 2022 | Variational Inference | —Unverified | 0 | 0 |
| Learning to Dequantise with Truncated Flows | Sep 29, 2021 | Variational Inference | —Unverified | 0 | 0 |
| Learning to Forget: Bayesian Time Series Forecasting using Recurrent Sparse Spectrum Signature Gaussian Processes | Dec 27, 2024 | Gaussian ProcessesGPU | —Unverified | 0 | 0 |
| Learning to Learn Dense Gaussian Processes for Few-Shot Learning | Dec 1, 2021 | Few-Shot LearningGaussian Processes | —Unverified | 0 | 0 |
| Towards Causal Representation Learning and Deconfounding from Indefinite Data | May 4, 2023 | Causal DiscoveryDisentanglement | —Unverified | 0 | 0 |
| Probabilistic Test-Time Generalization by Variational Neighbor-Labeling | Jul 8, 2023 | Domain GeneralizationVariational Inference | —Unverified | 0 | 0 |
| Learning with Importance Weighted Variational Inference: Asymptotics for Gradient Estimators of the VR-IWAE Bound | Oct 15, 2024 | Variational Inference | —Unverified | 0 | 0 |
| Less Suboptimal Learning and Control in Variational POMDPs | Mar 9, 2021 | Model-based Reinforcement Learningreinforcement-learning | —Unverified | 0 | 0 |
| Leveraging Bayesian Analysis To Improve Accuracy of Approximate Models | May 20, 2019 | Uncertainty QuantificationVariational Inference | —Unverified | 0 | 0 |
| LIA: Latently Invertible Autoencoder with Adversarial Learning | Sep 25, 2019 | DecoderGenerative Adversarial Network | —Unverified | 0 | 0 |
| Lifted Tree-Reweighted Variational Inference | Jun 17, 2014 | Variational Inference | —Unverified | 0 | 0 |
| Likelihood approximations via Gaussian approximate inference | Oct 28, 2024 | Variational Inference | —Unverified | 0 | 0 |
| Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation | Apr 16, 2023 | NeRFObject | —Unverified | 0 | 0 |