ComputationalRadiationPhysics / InFlow
☆11Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for InFlow
- Code for the research paper "HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference".☆21Updated 3 years ago
- Code for the paper "Analyzing inverse problems with invertible neural networks." (2018)☆84Updated 4 years ago
- ☆32Updated 2 years ago
- Code for the paper "Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification" (2020)☆42Updated 6 months ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆49Updated 3 months ago
- ☆28Updated 2 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- ☆22Updated 4 years ago
- AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation☆15Updated 4 years ago
- Pytorch implementation of the basic idea presented in https://arxiv.org/abs/2002.07101☆11Updated 4 years ago
- ☆23Updated 3 years ago
- Normalizing Flows with a resampled base distribution☆44Updated 2 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆72Updated last year
- Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch☆22Updated 4 years ago
- Code for experiments to learn uncertainty☆30Updated last year
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 3 years ago
- Code for Understanding and Mitigating Exploding Inverses in Invertible Neural Networks (AISTATS 2021) http://arxiv.org/abs/2006.09347☆28Updated 4 years ago
- beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022☆36Updated 2 years ago
- Development and evaluation of different approaches for fibre tracking of diffusion weighted MRI data.☆11Updated 2 years ago
- [AISTATS2020] The official repository of "Invertible Generative Modling using Linear Rational Splines (LRS)".☆20Updated last year
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆47Updated 4 years ago
- Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with…☆52Updated last year
- ☆86Updated 3 years ago
- Implementations of orthogonal and semi-orthogonal convolutions in the Fourier domain with applications to adversarial robustness☆42Updated 3 years ago
- PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows☆30Updated 3 years ago
- ☆15Updated 2 years ago
- ☆45Updated last year
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- ☆18Updated 2 years ago
- ☆53Updated 3 months ago