BayesFlow: Learning Complex Stochastic Models With Invertible Neural Networks | 0 | 0.34 | 2022 |
Towards Multimodal Depth Estimation from Light Fields | 0 | 0.34 | 2022 |
Generative Classifiers as a Basis for Trustworthy Image Classification | 0 | 0.34 | 2021 |
Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging | 0 | 0.34 | 2021 |
Learning Robust Models Using the Principle of Independent Causal Mechanisms. | 0 | 0.34 | 2021 |
Conditional Invertible Neural Networks for Diverse Image-to-Image Translation. | 0 | 0.34 | 2020 |
Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification | 0 | 0.34 | 2020 |
Out Of Distribution Detection For Intra-Operative Functional Imaging | 0 | 0.34 | 2019 |
Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks. | 1 | 0.38 | 2019 |
HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference. | 0 | 0.34 | 2019 |
Analyzing Inverse Problems with Invertible Neural Networks. | 0 | 0.34 | 2019 |
Analyzing Inverse Problems with Invertible Neural Networks. | 0 | 0.34 | 2019 |
Analyzing Inverse Problems with Invertible Neural Networks. | 2 | 0.37 | 2018 |