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Ari Morcos

Ari Morcos



Ari Morcos is a research scientist at Meta AI Research (FAIR Team) in Menlo Park working on understanding the mechanisms underlying neural network computation and function, and using these insights to build machine learning systems more intelligently. Most recently, his work has focused on understanding properties of data and how these properties lead to desirable and useful representations. He has worked on a variety of topics, including self-supervised learning, the lottery ticket hypothesis, the mechanisms underlying common regularizers, and the properties predictive of generalization, as well as methods to compare representations across networks, the role of single units in computation, and on strategies to induce and measure abstraction in neural network representations.

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