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"Pitfalls of Climate Network Construction: A Statistical Perspective". With Moritz H and Bedartha Goswami, we show that many observations in climate networks might be spurious artifacts. And I am sure the same would hold for brain networks. doi.org/10.1175/JCLI-D…

Many thanks to the organizers! I learned a lot, gained many new perspectives and had a lot of fun along the way! An invaluable experience.

Can kernel methods and wide neural networks overfit benignly in fixed dimension? In our NeurIPS 2023 paper with Moritz H, Ulrike Luxburg, and Ingo Steinwart, we prove: yes, but only with some non-standard modifications. 1/ 🧵

📷 Benign overfitting even works in small, fixed dimension! Not with ReLu activation function or smooth kernels, but with extra-spiky variants. #neurips2023 paper with Moritz H, David Holzmüller, Ingo Steinwart: arxiv.org/abs/2305.14077

I will present our work on benign overfitting of kernels and neural networks at #NeurIPS2023 on Thursday 5pm (#1724). Feel free to reach out if you want to chat about (deep) learning theory towards principled deep learning, also beyond kernels. Find a thread below.