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CiteME
PublicCiteME is a benchmark designed to test the abilities of language models in finding papers that are cited in scientific texts.- Python package to corrupt arbitrary images.
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Publicmodel-vs-human
PublicBenchmark your model on out-of-distribution datasets with carefully collected human comparison data (NeurIPS 2021 Oral)foolbox
PublicA Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAXbwki-weekly-tasks
PublicDataTypeIdentification
Publicrobustness
PublicRobustness and adaptation of ImageNet scale models. Pre-Release, stay tuned for updates.game-of-noise
Publictools
Publicslurm-monitoring-public
PublicAnalysisBySynthesis
Publicinference_results_v1.1
Publicslow_disentanglement
Publicstylize-datasets
Publictesting_visualizations
Public archiveCode for the paper " Exemplary Natural Images Explain CNN Activations Better than Feature Visualizations"openimages2coco
PublicDeepLabCut
Publicmagapi-wrapper
PublicWrapper around Microsoft Academic Knowledge API to retrieve MAG datasiamese-mask-rcnn
PublicSiamese Mask R-CNN model for one-shot instance segmentationmmdetection
Public- Code, data and benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (NeurIPS 2019 ML4AD)
texture-vs-shape
Publicfoolbox-zoo-dummy
Publicdocker-deeplearning
Publicdefensive-distillation
Publicmnist_challenge
Public