most citedCapabilities of Auto-encoders and Principal Component Analysis of the Reduction of Microstructural Images; Application on the Acceleration of Phase-Field Simulations

28 citations · 28 across the 1 of their papers we have counts for

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cs.LG2026★ 28 cited

Capabilities of Auto-encoders and Principal Component Analysis of the Reduction of Microstructural Images; Application on the Acceleration of Phase-Field Simulations

Seifallah Fetni, Thinh Quy Duc Pham, Truong Vinh Hoang +4

In this work, a data-driven framework based on Phase-Field simulations data is proposed to highlight the capabilities of neural networks to ensure accurate low dimensionality reduc…