Philipp Grohs

1. The Modern Mathematics of Deep Learning
   2021/05/09 by Julius Berner, Philipp Grohs, Gitta Kutyniok +1 · 6 voices · 1 citation
   Computer Science · Physics and Astronomy · Engineering · #Neural Networks and Applications #Model Reduction and Neural Networks #Sparse and Compressive Sensing Techniques
2. Deep Neural Network Approximation Theory
   2021/02/24 by Dennis Elbrächter, Dennis Elbrachter, Dmytro Perekrestenko +3 · 17 citations
   Computer Science · Mathematics · #Image and Signal Denoising Methods #Neural Networks and Applications #Mathematical Approximation and Integration
3. Phase retrieval in the general setting of continuous frames for Banach\n spaces
   2016/04/11 by Rima Alaifari, Philipp Grohs, Alaifari, Rima +1 · 6 citations
   Computer Science · Engineering · Physics and Astronomy · #Advanced X-ray Imaging Techniques #FOS: Mathematics #Functional Analysis (math.FA) #Optical measurement and interference techniques #Welding Techniques and Residual Stresses
4. Stable Phase Retrieval in Infinite Dimensions
   2016/08/31 by Rima Alaifari, Ingrid Daubechies, Alaifari, Rima +5 · 4 citations
   Computer Science · Earth and Planetary Sciences · Physics and Astronomy · #Advanced X-ray Imaging Techniques #FOS: Mathematics #Functional Analysis (math.FA) #Optical measurement and interference techniques #Seismic Imaging and Inversion Techniques
5. Approximations with deep neural networks in Sobolev time-space
   2020/12/23 by Ahmed Abdeljawad, Philipp Grohs, Abdeljawad, Ahmed +1 · 4 citations
   Computer Science · Engineering · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Functional Analysis (math.FA) #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Numerical methods in engineering
6. Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems
   2025/04/08 by Michael Scherbela, Nicholas Gao, Scherbela, Michael +5 · 1 voice · 7 citations
   Materials Science · Physics and Astronomy · Biochemistry, Genetics and Molecular Biology · #Machine Learning in Materials Science #Advanced Chemical Physics Studies #Advanced Electron Microscopy Techniques and Applications
7. Deep neural network approximation for high-dimensional parabolic Hamilton-Jacobi-Bellman equations
   2021/03/09 by Philipp Grohs, Lukas Herrmann, Grohs, Philipp +1 · 2 citations
   Physics and Astronomy · Computer Science · Economics, Econometrics and Finance · #Model Reduction and Neural Networks #Reinforcement Learning in Robotics #Stochastic processes and financial applications
8. Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?
   2022/05/19 by Leon Gerard, Michael Scherbela, Gerard, Leon +5 · 2 citations
   Materials Science · Physics and Astronomy · Chemical Engineering · #Machine Learning in Materials Science #Advanced Chemical Physics Studies #Catalysis and Oxidation Reactions
9. DeepErwin
   2023/03/17 by Michael Scherbela, Scherbela, Michael, Leon Gerard +3 · 1 citation
   Materials Science · Chemistry · Physics and Astronomy · #Machine Learning in Materials Science #Advanced NMR Techniques and Applications #Advanced Chemical Physics Studies
10. Variational Monte Carlo on a Budget -- Fine-tuning pre-trained Neural Wavefunctions
    2023/07/15 by Michael Scherbela, Leon Gerard, Scherbela, Michael +3 · 1 citation
    Materials Science · Chemical Engineering · #Machine Learning in Materials Science #X-ray Diffraction in Crystallography #Catalysis and Oxidation Reactions