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This blog post accompanies our recent paper PFT: Phonon Fine-tuning for Machine Learned Interatomic Potentials.
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Note: this is condensed version of a project for course 6.7960.
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One interesting application area of AI in the sciences is quantum chemistry.
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Gradient-descent-based optimizers have long been used as the optimization algorithm of choice for deep learning models.
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When training a Deep Learning model, one must often read and pre-process data before it can be passed through the model.
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Google AI recently released a paper, Rethinking Attention with Performers (Choromanski et al., 2020), which introduces Performer, a Transformer architecture which estimates the full-rank-attention mechanism using orthogonal random features to approximate…
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Since the 1940s, electric guitarists, keyboardists, and other instrumentalists have been using effects pedals, devices that modify the sound of the original audio source.
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This post is the first in a series of articles about natural language processing (NLP), a subfield of machine learning concerning the interaction between computers and human language.
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Inspired by the story of Bill Benter, a gambler who developed a computer model that made him close to a billion dollars (Chellel, 2018) betting on horse races in the Hong Kong Jockey Club (HKJC), I set out to see if I could use machine learning to identify
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In this post we will be using a method known as transfer learning in order to detect metastatic cancer in patches of images from digital pathology scans.