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What is the significance of Explainable Artificial Intelligence (XAI) in the face of impending EU AI regulations?
Join us as we delve into the latest advancements of this topic at our next AI Paper Spotlights - Berlin’s AI Research Meet Up, hosted by Merantix Momentum
In an era where machine learning models hold increasing sway, understanding their interpretations across different domains is paramount. Yet, relying solely on pixel-wise heat maps often falls short in bolstering analysts' insights. Our aim is to dissect the intricate structures that neural networks grasp, particularly when handling graph data.
About our speakers: Thomas Schnake is a PhD student at the @Technical University of Berlin and @BIFOLD. With a robust background in mathematics and scientific computing, Thomas focuses his research on crafting explainable AI solutions tailored to specific applications, notably in quantum chemistry and natural language processing. Delightfully, he has recently published a Journal paper at IEEE TPAMI and presented two ICML papers between 2021 and today.
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💻 You can also join us online here: https://lnkd.in/ej5bGsAs
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