wgao9 / mixed_KSGLinks
☆37Updated 8 years ago
Alternatives and similar repositories for mixed_KSG
Users that are interested in mixed_KSG are comparing it to the libraries listed below
Sorting:
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- General Latent Feature Modeling for Heterogeneous data☆50Updated last year
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆141Updated 9 years ago
- A deep generative model of semi-unsupervised learning☆15Updated 7 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Variational Fourier Features☆86Updated 4 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆34Updated 10 years ago
- ☆40Updated 6 years ago
- gpbo☆25Updated 4 years ago
- InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy☆148Updated last year
- Neural Processes implementation for 1D regression☆64Updated 6 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 6 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 7 years ago
- Implementation of linear CorEx and temporal CorEx.☆36Updated 4 years ago
- Deep Markov Models☆132Updated 6 years ago
- A Python library for reinforcement learning using Bayesian approaches☆53Updated 10 years ago
- Code for "Towards a learning theory of cause-effect inference" (ICML 2015).☆30Updated 5 years ago
- ☆125Updated 4 years ago
- Dirichlet MLE python library☆117Updated 5 months ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 6 years ago
- Code for doubly stochastic gradients☆26Updated 11 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆38Updated 4 years ago
- Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.☆40Updated 4 years ago
- ☆11Updated 8 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆33Updated 4 years ago
- Structural Causal Bandit☆26Updated 4 years ago
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆100Updated 6 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 9 years ago