| NNgen/nngen |
281 |
|
0 |
0 |
over 2 years ago |
5 |
September 12, 2023 |
31 |
apache-2.0 |
Python |
| NNgen: A Fully-Customizable Hardware Synthesis Compiler for Deep Neural Network |
| KristiyanVachev/Leaf-Question-Generation |
104 |
|
0 |
0 |
about 4 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| Easy to use and understand multiple-choice question generation algorithm using T5 Transformers. |
| TrustAI/DeepConcolic |
85 |
|
0 |
0 |
over 4 years ago |
0 |
|
2 |
bsd-3-clause |
Python |
| Concolic Testing for Deep Neural Networks |
| dlsys-course/assignment2-2017 |
59 |
|
0 |
0 |
almost 9 years ago |
0 |
|
0 |
|
Python |
| (Spring 2017) Assignment 2: GPU Executor |
| uvipen/Deeplab-pytorch |
58 |
|
0 |
0 |
about 7 years ago |
0 |
|
2 |
mit |
Python |
| Deeplab for semantic segmentation tasks |
| testingautomated-usi/uncertainty-wizard |
39 |
|
0 |
0 |
about 3 years ago |
11 |
May 03, 2022 |
6 |
mit |
Python |
| Uncertainty-Wizard is a plugin on top of tensorflow.keras, allowing to easily and efficiently create uncertainty-aware deep neural networks. Also useful if you want to train multiple small models in parallel. |
| bethgelab/adversarial-vision-challenge |
36 |
|
0 |
0 |
over 7 years ago |
18 |
September 17, 2018 |
8 |
|
Python |
| NIPS Adversarial Vision Challenge |
| nathanbreitsch/torchmocks |
24 |
|
0 |
0 |
almost 3 years ago |
0 |
|
0 |
mit |
Python |
| Test pytorch code with minimal computational overhead |
| pityka/lamp |
21 |
|
0 |
4 |
over 2 years ago |
62 |
May 18, 2022 |
29 |
other |
Scala |
| deep learning and scientific computing framework with native CPU and GPU backend for the Scala programming language |
| kupl/adapt |
18 |
|
0 |
0 |
about 3 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| ADAPT is the open source white-box testing framework for deep neural networks |
