Excited to introduce GraphXAI - a general-purpose framework that provides an ecosystem of XAI-ready synthetic and real-world graph datasets with ground-truth explanations, a visualizer, and a set of evaluation metrics to benchmark the quality of any given GNN explanation. [1/N]

Stoked to host our first installment of this exciting seminar series here at Harvard!

🚨Announcing the next Harvard #efficientml eminar on Machine Unlearning, featuring Nicolas Papernot and Rising Star Anvith Thudi! 🧠 ➡️ March 25 @ 2:30pm ET 📅 Registration: tinyurl.com/5n8kke2a 🔗 Website: efficientml.org Harvard Data Science Initiative DBMI at Harvard Med Kempner Institute at Harvard University

A driving force of competition between top AI companies is dataset expansion. But is bigger really better? cohere's Sara Hooker argues scaling could be inefficient. Jonathan Richard Schwarz of DBMI at Harvard Med believes smaller models can adapt. From Nina Pasquini: #harvard harvardmagazine.com/2024/03/scalin…

Our Marinka Zitnik lab team at the Harvard CMSA 2024 Ding Shum lecture by Yann LeCun today. We missed getting a photo with the brilliant speaker himself – but maybe that’s another incentive to invite Yann LeCun back to Harvard again? 😁 1/4

🚨Announcing the next Harvard #efficientml seminar on Learning to learn, featuring Jane Wang and Rising Star Julian Coda-Forno ! 🧠 ➡️ April 22, 2:30 ET 📅Registration: tinyurl.com/yyzt9c96 🔗 Website: efficientml.org Harvard Data Science Initiative DBMI at Harvard Med Kempner Institute at Harvard University