BAE2. theta| phi #191
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table.AGENT_ENVIRONMENT2has learn and growth structure of new startup
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updated based on this gp which combined #190 on top of
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In pure digital industry (academia), I'm asking for help to scholars who satisfies the following condition:
Just like Strategy dynamics: Agency, path dependency, and self-organized emergence studies Danone's pivot along its 42 year trajectory, I tend to follow up with 10 years of research trajectory of professors at scale (Cathy Wu, Vikash Mansinghka, Kris Ferreira) and sail (Charlie Fine, Scott Stern, Andrew Gelman) stage. scale - CathyHere's the table summarizing Cathy Wu's research trajectory, mapping the year, need, responsive solution, and corresponding papers. I intend to keep updating the table, so flagging factually wrong information would be really helpful.
This table highlights how Cathy Wu's research has consistently evolved to address emerging needs in transportation, from estimating traffic flow and understanding the impact of autonomous vehicles to developing scalable, modular, and transferable learning methods for increasingly complex transportation problems. Her work showcases a focus on real-world deployment challenges and a drive to develop AI-driven solutions that can adapt to the ever-changing landscape of intelligent transportation systems. |
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using ten standards on good bayesian model, we can compare learning algorithms of each startup based on business model
examples:
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