robustness
Neural network trainer
A library for training and evaluating neural networks with a focus on adversarial robustness.
A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.
921 stars
19 watching
182 forks
Language: Jupyter Notebook
last commit: 11 months ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 eth-sri/diffai | Trains neural networks to be provably robust against adversarial examples using abstract interpretation techniques. | 219 |
 neuralhydrology/neuralhydrology | A Python library for training neural networks with focus on hydrological applications using PyTorch. | 372 |
 intelligent-machine-learning/dlrover | Automates large-scale deep learning training on distributed clusters, providing fault tolerance and fast recovery from failures. | 1,302 |
 borealisai/advertorch | A toolbox for researching and evaluating robustness against attacks on machine learning models | 1,311 |
 open-mmlab/mmengine | Provides a flexible and configurable framework for training deep learning models with PyTorch. | 1,196 |
 wyy-123-xyy/ra-fed | A Python implementation of a distributed machine learning framework for training neural networks on multiple GPUs | 6 |
 robustbench/robustbench | A standardized benchmark for measuring the robustness of machine learning models against adversarial attacks | 682 |
 guanghelee/neurips19-certificates-of-robustness | Provides a framework for computing tight certificates of adversarial robustness for randomly smoothed classifiers. | 17 |
 jedld/brains-jruby | An implementation of a feedforward neural network toolkit for JRuby | 60 |
 imistyrain/matconvnet-oneclick | A tool to train and deploy convolutional neural networks in MATLAB using MatConvNet | 87 |
 ahmedfgad/neuralgenetic | Trains artificial neural networks using the genetic algorithm | 241 |
 molcik/python-neuron | A Python library for implementing and training various neural network architectures | 40 |
 loudinthecloud/dpwa | A distributed learning framework that enables peer-to-peer parameter averaging and asynchronous training of deep neural networks | 53 |
 paarthneekhara/rnn_adversarial_reprogramming | Repurposes pre-trained neural networks for new classification tasks through adversarial reprogramming of their inputs. | 6 |
 mikecmpbll/rann | Provides objects and algorithms for designing, processing and training Artificial Neural Networks in Ruby. | 3 |