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cs.LG2025
Smooth Model Compression without Fine-Tuning
Christina Runkel, Natacha Kuete Meli, Jovita Lukasik +3
Compressing and pruning large machine learning models has become a critical step towards their deployment in real-world applications. Standard pruning and compression techniques ar…
cs.LG2024
Continuous Learned Primal Dual
Christina Runkel, Ander Biguri, Carola-Bibiane Schönlieb
Neural ordinary differential equations (Neural ODEs) propose the idea that a sequence of layers in a neural network is just a discretisation of an ODE, and thus can instead be dire…