vislearn / inn_toy_dataLinks
Code for artificial toy data sets used to evaluate (conditional) invertible neural networks and related methods
☆12Updated 4 years ago
Alternatives and similar repositories for inn_toy_data
Users that are interested in inn_toy_data are comparing it to the libraries listed below
Sorting:
- Code for the paper "Analyzing inverse problems with invertible neural networks." (2018)☆103Updated 5 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- ☆54Updated last year
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆57Updated last year
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆78Updated 2 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 5 years ago
- ☆22Updated last year
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 5 years ago
- Noise Contrastive Estimation (NCE) in PyTorch☆32Updated 10 months ago
- Code for the research paper "HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference".☆22Updated 4 years ago
- ☆18Updated 5 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆47Updated 2 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 3 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 6 years ago
- Featurized Density Ratio Estimation☆20Updated 4 years ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆18Updated 3 years ago
- ☆11Updated 4 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆35Updated 4 years ago
- ☆33Updated 3 years ago
- Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch☆23Updated 5 years ago
- Pytorch Implementation of variational auto-encoder for MNIST☆61Updated 7 years ago
- Pytorch implementation of the basic idea presented in https://arxiv.org/abs/2002.07101☆12Updated 5 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆26Updated 5 years ago
- Reproducing the paper "Variational Sparse Coding" for the ICLR 2019 Reproducibility Challenge☆62Updated 2 years ago
- Code for the paper "Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification" (2020)☆43Updated last year
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 3 years ago
- [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…☆14Updated 3 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 4 years ago
- Code for Understanding and Mitigating Exploding Inverses in Invertible Neural Networks (AISTATS 2021) http://arxiv.org/abs/2006.09347☆30Updated 5 years ago