Ben Adcock

1. The troublesome kernel -- On hallucinations, no free lunches and the accuracy-stability trade-off in inverse problems
   2020/01/05 by Nina Maria Gottschling, Nina M. Gottschling, Vegard Antun +6 · 1 voice · 8 citations
   Computer Science · Engineering · Medicine · #65M12 #65R32 #68T05 #94A08 #Advanced X-ray and CT Imaging #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Medical Imaging Techniques and Applications #Sparse and Compressive Sensing Techniques #cs.CV #cs.LG
2. The gap between theory and practice in function approximation with deep neural networks
   2020/01/16 by Ben Adcock, Nick Dexter, Adcock, Ben +1 · 5 citations
   Engineering · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Non-Destructive Testing Techniques #Numerical Analysis (math.NA) #Sparse and Compressive Sensing Techniques
3. On the consistent reasoning paradox of intelligence and optimal trust in AI: The power of 'I don't know'
   2024/08/05 by Alexander Bastounis, Bastounis, Alexander, Paolo Campodonico +7 · 2 voices · 2 citations
   #cs.AI #cs.LG #math.OC #math.PR
4. On the numerical stability of Fourier extensions
   2012/06/19 by Ben Adcock, Daan Huybrechs, Adcock, Ben +3 · 2 citations
   Computer Science · Physics and Astronomy · #Digital Filter Design and Implementation #FOS: Mathematics #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Numerical Methods and Algorithms
5. Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data
   2020/12/11 by Ben Adcock, Simone Brugiapaglia, Adcock, Ben +5 · 2 citations
   Physics and Astronomy · Decision Sciences · Computer Science · #Model Reduction and Neural Networks #Probabilistic and Robust Engineering Design #Neural Networks and Applications
6. Near-optimal sampling strategies for multivariate function approximation on general domains
   2019/08/04 by Ben Adcock, Juan M. Cardenas, Adcock, Ben +1 · 2 citations
   Computer Science · Decision Sciences · Mathematics · #FOS: Mathematics #Numerical Analysis (math.NA) #Numerical Methods and Algorithms #Probabilistic and Robust Engineering Design #Statistical and numerical algorithms
7. On the resolution power of Fourier extensions for oscillatory functions
   2011/05/17 by Ben Adcock, Daan Huybrechs, Adcock, Ben +1 · 2 citations
   Mathematics · Computer Science · #Mathematical functions and polynomials #Digital Filter Design and Implementation #Iterative Methods for Nonlinear Equations
8. Compressive Hermite interpolation: sparse, high-dimensional approximation from gradient-augmented measurements
   2017/12/18 by Ben Adcock, Adcock, Ben, Yi Sui +1 · 1 citation
   Engineering · Decision Sciences · Mathematics · #Sparse and Compressive Sensing Techniques #Probabilistic and Robust Engineering Design #Mathematical Approximation and Integration
9. Towards optimal sampling for learning sparse approximation in high dimensions
   2022/02/04 by Ben Adcock, Juan M. Cardenas, Adcock, Ben +5 · 1 citation
   Computer Science · Engineering · Mathematics · #Machine Learning and Algorithms #Sparse and Compressive Sensing Techniques #Mathematical Approximation and Integration
10. 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
11. 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
12. Restarts subject to approximate sharpness: A parameter-free and optimal scheme for first-order methods
    2023/01/05 by Ben Adcock, Matthew J. Colbrook, Adcock, Ben +3 · 1 citation
    Computer Science · Engineering · #65B99 #65K0 #68Q25 #90C25 #90C60 #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Optimization and Control (math.OC) #Photoacoustic and Ultrasonic Imaging #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
13. CAS4DL: Christoffel Adaptive Sampling for function approximation via Deep Learning
    2022/08/25 by Ben Adcock, Adcock, Ben, Juan M. Cardenas +3 · 1 citation
    Decision Sciences · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Probabilistic and Robust Engineering Design #Statistical Methods and Inference
14. 1-Lipschitz Neural Networks on Hadamard Manifolds
    2026/07/21 by Davide Murari, Marta Ghirardelli, Ben Adcock +3
    #math.NA #cs.LG #cs.NA