Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...
A new topology-based method predicts atomic charges in metal-organic frameworks from bond connectivity alone, making large-scale computational screening practical.
A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account ...
Graphs are everywhere. In discrete mathematics, they are structures that show the connections between points, much like a ...
Physicists have long recognized the value of photonic graph states in quantum information processing. However, the difficulty ...
Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...
This WSJ video investigation reveals how the video-centric social network is so good at figuring out interests you never expressly tell it.
Abstract: Detecting small targets in complex marine environments is challenging for radar systems. Existing methods relying on high-dimensional features often fail to account for correlations in radar ...
Abstract: Graph algorithms are important for many domains, and GPUs can be used to accelerate them. Unfortunately, CUDA code can only be run on NVIDIA GPUs. In this study, we port the CUDA graph codes ...
A production-grade algorithmic trading system combining particle filters, graph-based ecosystem modeling, RAG-grounded LLM research agents, and NLP news pipelines for NIFTY 50 swing trading (3-20 day ...
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