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Pre-trained models, data, code & materials from the paper "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness" (ICLR 2019 Oral)
Benchmark your model on out-of-distribution datasets with carefully collected human comparison data (NeurIPS 2021 Oral)
Code to create Stylized-ImageNet, a stylized version of standard ImageNet (ICLR 2019 Oral)
Code, data and benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (NeurIPS 2019 ML4AD)
Data, code & materials from the paper "Generalisation in humans and deep neural networks" (NeurIPS 2018)
Generate a customised list of publications for your LaTeX CV using BibTeX entries.
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