23 citations · 37 across the 16 of their papers we have counts for
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stat.ML2021
Saddle-to-Saddle Dynamics in Deep Linear Networks: Small Initialization Training, Symmetry, and Sparsity
Arthur Jacot, François Ged, Berfin Şimşek +2
The dynamics of Deep Linear Networks (DLNs) is dramatically affected by the variance of the parameters at initialization . For DLNs of width , we show a phase transit…
stat.ML2021
DNN-Based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel
Benjamin Dupuis, Arthur Jacot
We study the Solid Isotropic Material Penalisation (SIMP) method with a density field generated by a fully-connected neural network, taking the coordinates as inputs. In the large…