| tensorflow/probability |
4,028 |
|
126 |
316 |
over 2 years ago |
51 |
November 20, 2023 |
652 |
apache-2.0 |
Jupyter Notebook |
| Probabilistic reasoning and statistical analysis in TensorFlow |
| Moataz-Elmesmary/Data-Science-Roadmap |
2,445 |
|
0 |
0 |
over 2 years ago |
0 |
|
3 |
mit |
|
| Data Science Roadmap from A to Z |
| Machine-Learning-Tokyo/Interactive_Tools |
1,594 |
|
0 |
0 |
over 4 years ago |
0 |
|
1 |
|
|
| Interactive Tools for Machine Learning, Deep Learning and Math |
| ragulpr/wtte-rnn |
580 |
|
0 |
1 |
over 6 years ago |
5 |
October 23, 2018 |
33 |
mit |
Python |
| WTTE-RNN a framework for churn and time to event prediction |
| ikostrikov/pytorch-flows |
444 |
|
0 |
0 |
about 5 years ago |
0 |
|
5 |
mit |
Python |
| PyTorch implementations of algorithms for density estimation |
| dougbrion/pytorch-classification-uncertainty |
235 |
|
0 |
0 |
over 3 years ago |
0 |
|
3 |
mit |
Python |
| This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty" |
| kedartatwawadi/NN_compression |
189 |
|
0 |
0 |
almost 7 years ago |
0 |
|
6 |
mit |
Jupyter Notebook |
| LiamConnell/deep-algotrading |
145 |
|
0 |
0 |
over 8 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading |
| markus93/NN_calibration |
133 |
|
0 |
0 |
about 3 years ago |
0 |
|
6 |
mit |
Jupyter Notebook |
| Calibration of Convolutional Neural Networks |
| zhao-tong/GAug |
65 |
|
0 |
0 |
almost 5 years ago |
0 |
|
0 |
mit |
Python |
| AAAI'21: Data Augmentation for Graph Neural Networks |
