most citedPhysics-agnostic and Physics-infused machine learning for thin films flows: modeling, and predictions from small data

12 citations · 13 across the 3 of their papers we have counts for

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cs.LG2025

Attribution-Guided Distillation of Matryoshka Sparse Autoencoders

Cristina P. Martin-Linares, Jonathan P. Ling

Sparse autoencoders (SAEs) aim to disentangle model activations into monosemantic, human-interpretable features. In practice, learned features are often redundant and vary across t…

cs.LG2023★ 1 cited

Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points

Gianluca Fabiani, Nikolaos Evangelou, Tianqi Cui +4

We present a machine learning (ML)-assisted framework bridging manifold learning, neural networks, Gaussian processes, and Equation-Free multiscale modeling, for (a) detecting tipp…