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Scientific ML is more than applying ML to science — it's about letting domain structure shape the model itself. In this social, we bring together researchers working across domains (neuroscience, PDEs, physics simulations, and beyond) to discuss: What is the urgent 'X' in your X-informed AI? How do you identify the right inductive bias? How do we build a community that supports this? Come share how your domain shapes your models.
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