Anders C. Hansen
Orcid: 0000-0003-2700-9446
According to our database1,
Anders C. Hansen
authored at least 36 papers
between 2010 and 2025.
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Bibliography
2025
Trustworthy AI in numerics: On verification algorithms for neural network-based PDE solvers.
CoRR, September, 2025
The Troublesome Kernel: On Hallucinations, No Free Lunches, and the Accuracy-Stability Tradeoff in Inverse Problems.
SIAM Rev., 2025
2024
On the consistent reasoning paradox of intelligence and optimal trust in AI: The power of 'I don't know'.
CoRR, 2024
Do stable neural networks exist for classification problems? - A new view on stability in AI.
CoRR, 2024
2023
When can you trust feature selection? - I: A condition-based analysis of LASSO and generalised hardness of approximation.
CoRR, 2023
Implicit regularization in AI meets generalized hardness of approximation in optimization - Sharp results for diagonal linear networks.
CoRR, 2023
The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning.
Proceedings of the Artificial Neural Networks and Machine Learning, 2023
2022
IEEE Trans. Signal Process., 2022
2021
The mathematics of adversarial attacks in AI - Why deep learning is unstable despite the existence of stable neural networks.
CoRR, 2021
Can stable and accurate neural networks be computed? - On the barriers of deep learning and Smale's 18th problem.
CoRR, 2021
2020
The troublesome kernel: why deep learning for inverse problems is typically unstable.
CoRR, 2020
2019
Non-uniform recovery guarantees for binary measurements and infinite-dimensional compressed sensing.
CoRR, 2019
CoRR, 2019
CoRR, 2019
Uniform recovery in infinite-dimensional compressed sensing and applications to structured binary sampling.
CoRR, 2019
CoRR, 2019
2017
On the Absence of Uniform Recovery in Many Real-World Applications of Compressed Sensing and the Restricted Isometry Property and Nullspace Property in Levels.
SIAM J. Imaging Sci., 2017
2016
On Asymptotic Incoherence and Its Implications for Compressed Sensing of Inverse Problems.
IEEE Trans. Inf. Theory, 2016
A Note on Compressed Sensing of Structured Sparse Wavelet Coefficients From Subsampled Fourier Measurements.
IEEE Signal Process. Lett., 2016
Found. Comput. Math., 2016
Analyzing the structure of multidimensional compressed sensing problems through coherence.
CoRR, 2016
2015
Linear Stable Sampling Rate: Optimality of 2D Wavelet Reconstructions from Fourier Measurements.
SIAM J. Math. Anal., 2015
Generalized sampling and the stable and accurate reconstruction of piecewise analytic functions from their Fourier coefficients.
Math. Comput., 2015
Can everything be computed? - On the Solvability Complexity Index and Towers of Algorithms.
CoRR, 2015
2014
SIAM J. Numer. Anal., 2014
SIAM J. Imaging Sci., 2014
On the absence of the RIP in real-world applications of compressed sensing and the RIP in levels.
CoRR, 2014
The quest for optimal sampling: Computationally efficient, structure-exploiting measurements for compressed sensing.
CoRR, 2014
2013
Beyond Consistent Reconstructions: Optimality and Sharp Bounds for Generalized Sampling, and Application to the Uniform Resampling Problem.
SIAM J. Math. Anal., 2013
Breaking the coherence barrier: asymptotic incoherence and asymptotic sparsity in compressed sensing
CoRR, 2013
Generalized sampling: stable reconstructions, inverse problems and compressed sensing over the continuum.
CoRR, 2013
2012
On optimal wavelet reconstructions from Fourier samples: linearity and universality of the stable sampling rate
CoRR, 2012
2010