EPISODE · Apr 9, 2019 · 49 MIN
Deep Learning for Population Genetic Inference with Dan Schrider - TWiML Talk #249
from The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) · host Sam Charrington
Today we’re joined by Dan Schrider, assistant professor in the department of genetics at UNC Chapel Hill. My discussion with Dan starts with an overview of population genomics, looking into his application of ML in the field. We then dig into Dan’s paper “The Unreasonable Effectiveness of Convolutional Neural Networks in Population Genetic Inference,” which examines the idea that CNNs are capable of outperforming expert-derived statistical methods for some key problems in the field.
What this episode covers
Today we’re joined by Dan Schrider, assistant professor in the department of genetics at UNC Chapel Hill. My discussion with Dan starts with an overview of population genomics, looking into his application of ML in the field. We then dig into Dan’s paper “The Unreasonable Effectiveness of Convolutional Neural Networks in Population Genetic Inference,” which examines the idea that CNNs are capable of outperforming expert-derived statistical methods for some key problems in the field.
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Deep Learning for Population Genetic Inference with Dan Schrider - TWiML Talk #249
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