| ajbrock/BigGAN-PyTorch |
2,356 |
|
0 |
0 |
about 5 years ago |
0 |
|
30 |
mit |
Python |
| The author's officially unofficial PyTorch BigGAN implementation. |
| albermax/innvestigate |
1,175 |
|
1 |
1 |
over 2 years ago |
8 |
October 12, 2023 |
55 |
other |
Python |
| A toolbox to iNNvestigate neural networks' predictions! |
| openai/supervised-reptile |
950 |
|
0 |
0 |
almost 3 years ago |
0 |
|
14 |
mit |
JavaScript |
| Code for the paper "On First-Order Meta-Learning Algorithms" |
| Yonghongwei/Gradient-Centralization |
497 |
|
0 |
0 |
over 4 years ago |
0 |
|
4 |
|
Python |
| A New Optimization Technique for Deep Neural Networks |
| rtqichen/residual-flows |
256 |
|
0 |
0 |
over 2 years ago |
0 |
|
3 |
mit |
Python |
| code for "Residual Flows for Invertible Generative Modeling". |
| JonasGeiping/invertinggradients |
109 |
|
0 |
0 |
about 4 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| Algorithms to recover input data from their gradient signal through a neural network |
| alecwangcq/GraSP |
40 |
|
0 |
0 |
about 6 years ago |
0 |
|
1 |
mit |
Python |
| Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH |
| hushell/sib_meta_learn |
37 |
|
0 |
0 |
about 6 years ago |
0 |
|
0 |
|
Python |
| Code of Empirical Bayes Transductive Meta-Learning with Synthetic Gradients |
| IBM/CLEVER-Robustness-Score |
16 |
|
0 |
0 |
over 7 years ago |
0 |
|
1 |
other |
Python |
| Codes for reproducing the robustness evaluation scores in “Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach,” ICLR 2018 |
| ryoasu/grad-cam |
11 |
|
0 |
0 |
over 6 years ago |
0 |
|
0 |
|
Python |
| Grad-CAM (Gradient-weighted Class Activation Mapping) |
