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  1. 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)

    R 668 94

  2. Benchmark your model on out-of-distribution datasets with carefully collected human comparison data (NeurIPS 2021 Oral)

    Python 178 18

  3. Code to create Stylized-ImageNet, a stylized version of standard ImageNet (ICLR 2019 Oral)

    Python 420 58

  4. Code, data and benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (NeurIPS 2019 ML4AD)

    Jupyter Notebook 152 23

  5. Data, code & materials from the paper "Generalisation in humans and deep neural networks" (NeurIPS 2018)

    R 83 20

  6. Generate a customised list of publications for your LaTeX CV using BibTeX entries.

    TeX 60 13

396 contributions in the last year

May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Mon Wed Fri

Contribution activity

May 2022

Created 1 commit in 1 repository
17 contributions in private repositories May 2 – May 13

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