Journalists have uncovered a handful of preprint academic studies with hidden prompts instructing A.I. reviewers to give ...

An efficient parallel algorithm for a new permutation generation method is presented. The crucial task in our permutation generation algorithm is starter sets generation where listing n! permutation ...

Learn how sidechains expand blockchain scalability and functionality: Explore their origins, bridging models, consensus types, security trade-offs, and major networks like Polygon, RSK, and ...

WG21-P3179R9 Parallel Range Algorithms WG21-P3709R2 Reconsider Parallel ranges::rotate_copy And ranges::reverse_copy Note: If these links appear to be broken, don't worry! Papers are often revised ...

sampling stan probabilistic-models pystan sampling-methods model-based loopy-belief-propagation ancestral-inference model-based-machine-learning probabilistic-machine-learning ...

Herein, we propose a simple and efficient equivariant model, EquiREANN, to effectively represent a nonlocal potential energy surface. It relies on a physically inspired message-passing framework, ...

Graph-based message-passing neural networks (MPNNs) have been proposed to facilitate computational research on materials at the atomic scale, which represent the chemical structure as an indirect ...

In this work, we present a machine learning approach to generate a new class of low-discrepancy point sets named Message-Passing Monte Carlo (MPMC) points. Motivated by the geometric nature of ...

OGNNMDA: a computational model for microbe-drug association prediction based on ordered message-passing graph neural networks ...

Message passing algorithms on graphical models offer a low-complexity and distributed paradigm for performing marginalization from a high-dimensional distribution. However, the convergence behaviors ...

Learn what message passing and shared memory are, how they differ, and how to use them for parallel programming on multiple processors or machines.