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:
- ☆40Updated 6 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- ☆125Updated 4 years ago
- InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy☆147Updated last year
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆100Updated 6 years ago
- General Latent Feature Modeling for Heterogeneous data☆50Updated last year
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆141Updated 9 years ago
- Deep Markov Models☆134Updated 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
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆38Updated 4 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆151Updated 6 years ago
- Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017☆36Updated 6 years ago
- Adaptive Neural Trees☆155Updated 6 years ago
- ☆43Updated 7 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Neural Processes implementation for 1D regression☆64Updated 6 years ago
- Implementation of linear CorEx and temporal CorEx.☆36Updated 4 years ago
- Automated Scalable Bayesian Inference☆131Updated 3 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 7 years ago
- gpbo☆25Updated 4 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.☆40Updated 4 years ago
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 6 years ago
- Code for doubly stochastic gradients☆26Updated 11 years ago
- Code and data for the experiments in "On Fairness and Calibration"☆51Updated 3 years ago
- Dirichlet MLE python library☆117Updated 3 months ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆54Updated 4 years ago
- Dirichlet Process K-means☆48Updated last year
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago