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Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametrization
Chris Kolb, Christian L. Müller, Bernd Bischl +1
We present a framework for smooth optimization of explicitly regularized objectives for (structured) sparsity. These non-smooth and possibly non-convex problems typically rely on s…
Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks
Suryanarayana Maddu, Dominik Sturm, Christian L. Müller +1
We characterize and remedy a failure mode that may arise from multi-scale dynamics with scale imbalances during training of deep neural networks, such as Physics Informed Neural Ne…
Learning physically consistent mathematical models from data using group sparsity
Suryanarayana Maddu, Bevan L. Cheeseman, Christian L. Müller +1
We propose a statistical learning framework based on group-sparse regression that can be used to 1) enforce conservation laws, 2) ensure model equivalence, and 3) guarantee symmetr…