Zobrazeno 1 - 10
of 227
pro vyhledávání: '"Wang, Dashun"'
Science has long been viewed as a key driver of economic growth and rising standards of living. Knowledge about how scientific advances support marketplace inventions is therefore essential for understanding the role of science in propelling real-wor
Externí odkaz:
http://arxiv.org/abs/2308.02933
Autor:
Gao, Jian, Wang, Dashun
The ongoing artificial intelligence (AI) revolution has the potential to change almost every line of work. As AI capabilities continue to improve in accuracy, robustness, and reach, AI may outperform and even replace human experts across many valuabl
Externí odkaz:
http://arxiv.org/abs/2304.10578
Interdisciplinary research has emerged as a hotbed for innovation and a key approach to addressing complex societal challenges. The increasing dominance of grant-supported research in shaping scientific advances, coupled with growing interest in fund
Externí odkaz:
http://arxiv.org/abs/2303.14732
Science progresses by building upon previous discoveries. It is commonly believed that the impact of scientific papers, as measured by citations, is positively correlated with the impact of past discoveries built upon. However, analyzing over 30 mill
Externí odkaz:
http://arxiv.org/abs/2303.03646
Despite the growing importance of teams in producing innovative and high-impact science and technology, it remains unclear how expertise diversity among team members relates to the originality and impact of the work they produce. Here, we develop a n
Externí odkaz:
http://arxiv.org/abs/2210.04422
Newton's centuries-old wisdom of standing on the shoulders of giants raises a crucial yet underexplored question: Out of all the prior works cited by a discovery, which one is its giant? Here, we develop a novel, discipline-independent method to iden
Externí odkaz:
http://arxiv.org/abs/2202.07862
Existing equivariant neural networks require prior knowledge of the symmetry group and discretization for continuous groups. We propose to work with Lie algebras (infinitesimal generators) instead of Lie groups. Our model, the Lie algebra convolution
Externí odkaz:
http://arxiv.org/abs/2109.07103
Extensive research has documented the immediate impacts of the COVID-19 pandemic on scientists, yet it remains unclear if and how such impacts have shifted over time. Here we compare results from two surveys of principal investigators, conducted betw
Externí odkaz:
http://arxiv.org/abs/2107.13073
Scientists and inventors set the direction of their work amidst an evolving landscape of questions, opportunities, and challenges. This paper introduces a measurement framework to quantify how far researchers move from their existing research when pr
Externí odkaz:
http://arxiv.org/abs/2107.06476