Daniel Lokshtanov’s work explores the limits of what computers can solve, paving the way for advances in artificial intelligence and computational efficiency.
Improved Modeling and Generalization Capabilities of Graph Neural Networks With Legendre Polynomials
Abstract: LegendreNet is a novel graph neural network (GNNs) model that addresses stability issues present in traditional GNN models such as ChebNet, while also more effectively capturing higher-order ...
Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...
UC Santa Barbara computer scientist Daniel Lokshtanov is advancing fundamental understanding of computational efficiency through groundbreaking research on quasi-polynomial time algorithms, supported ...
Abstract: Temporal logic is a concise way of specifying complex tasks. However, motion planning to achieve temporal logic specifications is difficult, and existing methods struggle to scale to complex ...
Graphene and its molecular fragments, known as nanographenes, are key materials for next-generation organic electronics due ...
The degree to which someone trusts the information depicted in a chart can depend on their assumptions about who made the ...
Get here CBSE Maths important questions of Class 10 of Chapter-Wise for Board exam preparation. Get expert-curated questions ...
Discover what exponential growth is, learn how it differs from other growth types, and explore real-life examples like compounding interest and population growth.
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