| Machine-Learning-Tokyo/Interactive_Tools |
1,594 |
|
0 |
0 |
about 4 years ago |
0 |
|
1 |
|
|
| Interactive Tools for Machine Learning, Deep Learning and Math |
| 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" |
| markus93/NN_calibration |
133 |
|
0 |
0 |
almost 3 years ago |
0 |
|
6 |
mit |
Jupyter Notebook |
| Calibration of Convolutional Neural Networks |
| allenai/pnp |
68 |
|
0 |
0 |
over 7 years ago |
0 |
|
2 |
apache-2.0 |
Scala |
| Probabilistic Neural Programming |
| GSimas/Deep-LearningAI |
61 |
|
0 |
0 |
almost 8 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| 🇦🇮 Deep Learning AI course on Coursera (Andrew Ng) |
| jojonki/Pointer-Networks |
60 |
|
0 |
0 |
over 4 years ago |
0 |
|
1 |
|
Python |
| Pointer Networks is a new neural architecture to learn the conditional probability of an output sequence with elements that are discrete tokens corresponding to positions in an input sequence. |
| vangj/py-bbn |
54 |
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0 |
0 |
about 2 years ago |
49 |
March 08, 2021 |
3 |
apache-2.0 |
Jupyter Notebook |
| Inference in Bayesian Belief Networks using Probability Propagation in Trees of Clusters (PPTC) and Gibbs sampling |
| nilseuropa/ros_ncnn |
45 |
|
0 |
0 |
about 5 years ago |
0 |
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0 |
|
C++ |
| ROS wrapper for NCNN neural inference framework |
| JiajinChen/shinyBN |
36 |
|
0 |
0 |
over 3 years ago |
0 |
|
1 |
apache-2.0 |
R |
| shinyBN: An online application for interactive Bayesian network inference and visualization |
| jostmey/RestrictedBoltzmannMachine |
35 |
|
0 |
0 |
over 5 years ago |
0 |
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1 |
|
Julia |
| Neural network trained as a generative model on the MNIST dataset using Persistent Contrastive Divergence. |
