#31: Deep Metric Learning, Generalization and Transformers with Karsten Roth
Update: 2022-11-27
Description
We are now the Transformative Ideas Podcast (formerly the ACIT Science Podcast)!
In this episode, we are joined by Karsten Roth. Karsten is a PhD Student at the Explainable Machine Learning group in Tuebingen, supervised by Zeynep Akata & Oriol Vinyals (https://karroth.com/).
His interests lie in most things Machine Learning and AI related.
We discuss ideas surrounding AI for medical applications, deep metric learning, generalization and representation learning, the surprising success of transformers, diffusion models, large language models and joint representations, generalization, inductive biases and neuroplasticity, AI research and bad incentives in the publishing culture, ML conferences, the interplay of industry and academia, advice for how to be a successful researchers, physics as a foundation for ML, and much more.
For inquiries, contact manu.brenn@gmail.com or reach out to me on Linkedin (https://www.linkedin.com/in/manuel-brenner-772261191/).
In this episode, we are joined by Karsten Roth. Karsten is a PhD Student at the Explainable Machine Learning group in Tuebingen, supervised by Zeynep Akata & Oriol Vinyals (https://karroth.com/).
His interests lie in most things Machine Learning and AI related.
We discuss ideas surrounding AI for medical applications, deep metric learning, generalization and representation learning, the surprising success of transformers, diffusion models, large language models and joint representations, generalization, inductive biases and neuroplasticity, AI research and bad incentives in the publishing culture, ML conferences, the interplay of industry and academia, advice for how to be a successful researchers, physics as a foundation for ML, and much more.
For inquiries, contact manu.brenn@gmail.com or reach out to me on Linkedin (https://www.linkedin.com/in/manuel-brenner-772261191/).
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