lead students collectively write a survey paper on github
This course will discuss the research forefronts and breakthroughs of artificial intelligence in the field of biomedical related fields, including highly accurate protein structure prediction with AlphaFold, fast and energy-efficient neuromorphic deep learning with first-spike times, machine learning platform to estimate anti-SARS-CoV-2 activities, adversarial interference and its mitigations in privacy-preserving collaborative machine learning; machine learning and algorithm fairness in public and population health, and computer vision in healthcare
This course will discuss the research forefronts and breakthroughs of artificial intelligence in the field of biomedical related fields, including highly accurate protein structure prediction with AlphaFold, fast and energy-efficient neuromorphic deep learning with first-spike times, machine learning platform to estimate anti-SARS-CoV-2 activities, adversarial interference and its mitigations in privacy-preserving collaborative machine learning; machine learning and algorithm fairness in public and population health, and computer vision in healthcare
nature machine learning
Aviv Regev works
CSHL meeting talks
pipp workshop reports
https://www.cc.gatech.edu/~badityap/
https://www.biorxiv.org/content/10.1101/803205v2#readcube-epdf
https://www.nature.com/natmachintell/research-articles
Navigating the pitfalls of applying machine learning in genomics
https://www.nature.com/articles/s41576-021-00434-9
Collection of ML/AI pitfall papers
https://github.com/crazyhottommy/machine-learning-resource/blob/master/README.md
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