Magic Grant project ‘Synthesizing Novel Video from GANs’ featured in Engadget

On August 14, 2020, the tech outlet Engadget featured recent research produced by the Magic Grant ‘Synthesizing Novel Video from GANs’ developed by grantee Haotian Zhang, alongside Cristobal Sciutto under faculty direction from Maneesh Agrawala and Kayvon Fatahalian.’ The article titled “These AI-generated tennis matches are both eerie and impressive,” describes the system developed under

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The Launch of the ‘Documenting COVID-19’ Public Records Repository

The COVID-19 pandemic has upended American life and forced state and local governments to enact important policy decisions with incomplete or uncertain information. To help explain these decisions to the public, we’re launching an online repository of local, state and federal public records obtained through open-records requests called Documenting COVID-19 (documentingcovid19.io). We will provide these materials free-of-charge to

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The Brown Institute is Proud to Announce Its 2020-2021 Magic Grants

The Brown Institute for Media Innovation, a collaboration between Stanford University’s School of Engineering and Columbia Journalism School, is pleased to announce its 2020-2021 Magic Grant recipients. Every year, the Brown Institute awards $1M in grants and fellowships to foster new tools and modes of expression. This is the eighth cohort of grantees — each

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Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods

Authors Daniel Y. Fu, Mayee F. Chen, Frederic Sala, Sarah M. Hooper, Kayvon Fatahalian, Christopher Ré Abstract Weak supervision is a popular method for building machine learning models without relying on ground truth annotations. Instead, it generates probabilistic training labels by estimating the accuracies of multiple noisy labeling sources (e.g., heuristics, crowd workers). Existing approaches

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