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cs.LG2026
naPINN: Noise-Adaptive Physics-Informed Neural Networks for Recovering Physics from Corrupted Measurement
Hankyeol Kim, Pilsung Kang
Physics-Informed Neural Networks (PINNs) are effective methods for solving inverse problems and discovering governing equations from observational data. However, their performance…
cs.LG2025
COUNTDOWN: Contextually Sparse Activation Filtering Out Unnecessary Weights in Down Projection
Jaewon Cheon, Pilsung Kang
The growing size of large language models has created significant computational inefficiencies. To address this challenge, sparse activation methods selectively deactivates non-ess…