Brugiapaglia, Simone

1. Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data
   2020/12/11 by Ben Adcock, Adcock, Ben, Simone Brugiapaglia +5 · 2 citations
   Physics and Astronomy · Decision Sciences · Computer Science · #Model Reduction and Neural Networks #Probabilistic and Robust Engineering Design #Neural Networks and Applications
2. Compressed sensing approaches for polynomial approximation of high-dimensional functions
   2017/03/20 by Adcock, Ben, Brugiapaglia, Simone, Webster, Clayton G. · 1 citation
   #FOS: Mathematics #Numerical Analysis (math.NA)
3. Sparse recovery in bounded Riesz systems with applications to numerical\n methods for PDEs
   2020/05/14 by Simone Brugiapaglia, Brugiapaglia, Simone, Sjoerd Dirksen +5 · 1 citation
   Economics, Econometrics and Finance · Mathematics · Medicine · #FOS: Computer and information sciences #FOS: Mathematics #Hemodynamic Monitoring and Therapy #Information Theory (cs.IT) #Numerical Analysis (math.NA) #Numerical methods in inverse problems #Stochastic processes and financial applications
4. Learning smooth functions in high dimensions: from sparse polynomials to deep neural networks
   2024/04/04 by Adcock, Ben, Brugiapaglia, Simone, Dexter, Nick +1 · 2 citations
   #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA)
5. On efficient algorithms for computing near-best polynomial approximations to high-dimensional, Hilbert-valued functions from limited samples
   2022/03/25 by Ben Adcock, Adcock, Ben, Simone Brugiapaglia +5 · 1 citation
   Decision Sciences · Engineering · Mathematics · #Probabilistic and Robust Engineering Design #Sparse and Compressive Sensing Techniques #Mathematical Approximation and Integration
6. LASSO reloaded: a variational analysis perspective with applications to compressed sensing
   2022/05/13 by Berk, Aaron, Brugiapaglia, Simone, Hoheisel, Tim · 1 citation
   #49J53 #62J07 #90C25 #94A12 #94A20 #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Numerical Analysis (math.NA) #Optimization and Control (math.OC)
7. Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks
   2022/11/22 by Ben Adcock, Adcock, Ben, Simone Brugiapaglia +5 · 1 citation
   Engineering · Computer Science · #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Reservoir Engineering and Simulation Methods
8. A practical existence theorem for reduced order models based on convolutional autoencoders
   2024/02/01 by Franco, Nicola Rares, Brugiapaglia, Simone · 1 citation
   #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA)
9. Physics-informed deep learning and compressive collocation for high-dimensional diffusion-reaction equations: practical existence theory and numerics
   2024/06/03 by Brugiapaglia, Simone, Dexter, Nick, Karam, Samir +1 · 1 citation
   #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (cs.LG) #Numerical Analysis (math.NA)