8 citations · 8 across the 6 of their papers we have counts for
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stat.ML2023
Improved identification accuracy in equation learning via comprehensive -elimination and Bayesian model selection
Daniel Nickelsen, Bubacarr Bah
In the field of equation learning, exhaustively considering all possible equations derived from a basis function dictionary is infeasible. Sparse regression and greedy algorithms h…
cs.LG2023
Recent Methodological Advances in Federated Learning for Healthcare
Fan Zhang, Daniel Kreuter, Yichen Chen +10
For healthcare datasets, it is often not possible to combine data samples from multiple sites due to ethical, privacy or logistical concerns. Federated learning allows for the util…
cs.LG2023
A physics-informed neural network framework for modeling obstacle-related equations
Hamid El Bahja, Jan Christian Hauffen, Peter Jung +2
Deep learning has been highly successful in some applications. Nevertheless, its use for solving partial differential equations (PDEs) has only been of recent interest with current…