Elimination-compensation pruning for fully-connected neural networks | ScienceToStartup | ScienceToStartup

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References (32)

[1]

Enhancing Computational Efficiency of Numerical Simulation for Subsurface Fluid-Induced Deformation Using Deep Learning Reduced Order Models

2025E. Ballini, A. Cominelli et al.

[2]

Neural networks for solving partial differential equations, a comprehensive review of recent methods and applications

2025Ayoub Ed Dyyany, A. Jamea et al.

[3]

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"Introduce a novel pruning method for neural networks that compensates for weight removal by adjusting adjacent biases, enhancing model efficiency."

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Elimination-compensation pruning for fully-connected neural networks

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References (32)

Founder's Pitch

"Introduce a novel pruning method for neural networks that compensates for weight removal by adjusting adjacent biases, enhancing model efficiency."

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Elimination-compensation pruning for fully-connected neural networks

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References (32)

Founder's Pitch

"Introduce a novel pruning method for neural networks that compensates for weight removal by adjusting adjacent biases, enhancing model efficiency."

Commercial Viability Breakdown

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