| openai/iaf |
442 |
|
0 |
0 |
over 7 years ago |
0 |
|
13 |
mit |
Python |
| Code for reproducing key results in the paper "Improving Variational Inference with Inverse Autoregressive Flow" |
| hoangcuong2011/Good-Papers |
231 |
|
0 |
0 |
almost 7 years ago |
0 |
|
1 |
|
|
| I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers |
| KirkHadley/icml2015_papers |
143 |
|
0 |
0 |
almost 11 years ago |
0 |
|
0 |
|
Python |
| Links to ICML 2015 papers available on arxiv |
| debasishg/ml-readings |
94 |
|
0 |
0 |
over 4 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| A list of papers / videos / tutorials / blog posts on machine learning |
| facebookresearch/CausalSkillLearning |
21 |
|
0 |
0 |
over 4 years ago |
0 |
|
1 |
other |
Python |
| Codebase for project about unsupervised skill learning via variational inference and causality. |
| mgorinova/autoreparam |
20 |
|
0 |
0 |
almost 6 years ago |
0 |
|
1 |
apache-2.0 |
Python |
| Automatic Reparameterisation of Probabilistic Programs |
| valdersoul/GraphBTM |
19 |
|
0 |
0 |
over 7 years ago |
0 |
|
0 |
|
Python |
| Code for paper "GraphBTM: Graph Enhanced Autoencoded Variational Inference for Biterm Topic Model". Under preparation. |
| ngorbach/Variational_Gradient_Matching_for_Dynamical_Systems |
18 |
|
0 |
0 |
about 7 years ago |
0 |
|
1 |
|
Jupyter Notebook |
| Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems" |
| y0ast/VIMCO |
18 |
|
0 |
0 |
over 5 years ago |
0 |
|
0 |
mit |
Python |
| Implementation of "Variational Inference for Monte Carlo Objectives" |
| manuwhs/BayesianRNN |
16 |
|
0 |
0 |
about 8 years ago |
0 |
|
0 |
|
Jupyter Notebook |
| Reproducing the results of the paper "Bayesian Recurrent Neural Networks" by Fortunato et al. |
