Speaker
Philip Coleman Harris
(Massachusetts Inst. of Technology (US))
Description
In this talk, we will review recent deep learning strategies, and talk about the progression of deep learning embeddings of data. We then follow with this by talking about recent work on supervised and weak supervised learning approaches and how they can play an integral role in next generation physics searches. Finally, we will comment briefly on recent experimental trends at the LHC, and how these tools are being integrated for further use.
