Deep Neural Networks (DNNs) have achieved great success at solving numerous tasks, sometimes surpassing human performance. However, it is still not well understood how they represent data internally and what are the characteristics of these representations. In this talk we will present some research works that study internal representations of DNNs and leverage them for controlled text generation, representation learning and bias analysis.
Xavier Suau holds a PhD in Computer Vision and Machine Learning from BarcelonaTech. Before that, he graduated from BarcelonaTech in Telecommunications Engineering and from Supaéro (Toulouse, France) in Aeronautics and Space Engineering. He is currently a research scientist at Apple's ML Research team, where he conducts research in ML representation learning and robustness. Before joining Apple, Xavier was a co-founder of the start-up Gestoos, an AI centric company tackling human-machine interaction.