EntropyKV is an online, 100% attention-free key-value (KV) cache eviction policy designed to run long-context LLMs on consumer-grade GPUs. Traditional KV cache compression methods (e.g., H2O, SnapKV) ...
Purdue University’s Artificial Intelligence Microcredentials offer quick and convenient online courses that cover the fundamentals of artificial intelligence and its applications. Every course ...
Contributed by Laura Gagliardi; received April 30, 2025; accepted October 17, 2025; reviewed by Clémence Corminboeuf, Seyed Mohamad Moosavi, and Veronique Van Speybroeck This contribution is part of ...
Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, 999077 Hong Kong S.A.R., China ...
This repository contains a Monte-Carlo solver to train neural-network variational wavefunction to solve continuous-space Fermi systems [M Geier, K Nazaryan, T Zaklama, L Fu, Phys. Rev. B 112, 045119 ...
The success of a molecular dynamics simulation depends on the accuracy of the force field used to define the atomic interactions. It is challenging to train both classical and modern machine-learning ...
Physics-Informed Neural Networks (PINN) emerged as a powerful tool for solving scientific computing problems, ranging from the solution of Partial Differential Equations to data assimilation tasks.
Physics-Informed Neural Networks (PINN) are neural networks encoding the problem governing equations, such as Partial Differential Equations (PDE), as a part of the neural network. PINNs have emerged ...
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