Neurocat has been accepted into the NVIDIA AI Inception program! Being recognized by one of the giants in AI space showcases the potential of our soft...
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Two of our cats are soon going to give a talk about the current status of duality-based adversarial robustness verification. The content will strongly rely on the recent publication ”Training Verified Learners with Learned Verifiers” by K. Dvijotham et al. (DeepMind). If you are as excited about this topic as we are – take a look at the attached presentation draft!
Neurocat has been accepted into the NVIDIA AI Inception program! Being recognized by one of the giants in AI space showcases the potential of our soft...
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Proud to present the research paper contributed by colleagues at neurocat GmbH & Volkswagen AG. Risk Assessment for ML models is of paramount impo...
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Making AI models robust against adversarial attacks, unboxing the black-box models to make their decision-making process more explainable, and also wo...
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Neurocat was voted one of the 247 most promising German AI startups by the initiative for applied artificial intelligence. We are pleased to be part o...
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State-of-the-art neural networks are vulnerable to adversarial examples. This major problem for the safe deployment of ML models arises when minor inp...
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Since the beginning of 2019, neurocat’s manpower has more than doubled. With all teams growing fast, we significantly expanded our office space. Luc...
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