Computer Vision News Computer Vision News 30 byChristina Bornberg I mainly attended three of the workshops, since they match my research interest: climate change, remote sensing and representational alignment. So, let’s get started with my top 3 presentations! I want to start with “SNAP” which was presented by SueYeon Chung. SNAP stands for Spectral theory of Neural Prediction and Alignment. They show that regression-based neural predictivity can be analytically decomposed into a set of contributing factors such as spectral bias and task-model alignment. Another talk from the representation alignment session was given by David Lipshutz. His work focuses on quantifying (dis)similarity of neural representations. Based on their statement that representations are stochastic and dynamic, they use stochastic shape distances (SSD) as metrics to disentangle noisy dynamic systems with different recurrent interactions. Finally, I really enjoyed Emily Shuckburgh’s keynote in the Tackling Climate Change with Machine Learning workshop. She was speaking about different tasks that can be helped by decisionsupport systems, including parameterisations, predictions, classification, systems analysis, evidence synthesis and ethical design. Meet Christina (almost) every month on Computer Vision News with her regular column datascEYEnce. My First ICLR Workshops Hello everyone! I am Christina - I do research in deep learning applied to ophthalmology and soon also remote sensing. I am happy to give a quick summary of the ICLR workshop day, which I attended together with Ralph from RSIP Vision in my lovely hometown, Vienna!
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