Soft Recovery Through ℓ1, 2 Minimization with Applications in Recovery of Simultaneously Sparse and Low-Rank Matrice. - Axel Flinth (CoRR, 2016)

Multivariate α-molecules. - Axel Flinth; Martin Schäfer (J. Approx. Theory, 2016)

Optimal Choice of Weights for Sparse Recovery With Prior Information. - Axel Flinth (IEEE Trans. Inf. Theory, 2016)

Hierarchical restricted isometry property for Kronecker product measurements. - Ingo Roth; Axel Flinth; Richard Kueng; Jens Eisert; Gerhard Wunder (Allerton, 2018)

Approximate Recovery of Initial Point-like and Instantaneous Sources from Coarsely Sampled Thermal Fields via Infinite-Dimensional Compressed Sensing. - Axel Flinth; Ali Hashemi 002 (EUSIPCO, 2018)

Hierarchical Sparse Channel Estimation for Massive MIMO. - Gerhard Wunder; Ingo Roth; Mahdi Barzegar; Axel Flinth; Saeid Haghighatshoar; Giuseppe Caire; Gitta Kutyniok (WSA, 2018)

Sparse blind deconvolution and demixing through ℓ 1, 2-minimization. - Axel Flinth (Adv. Comput. Math., 2018)

Recovery of Binary Sparse Signals With Biased Measurement Matrices. - Axel Flinth; Sandra Keiper (IEEE Trans. Inf. Theory, 2019)

Low-Overhead Hierarchically-Sparse Channel Estimation for Multiuser Wideband Massive MIMO. - Gerhard Wunder; Stelios Stefanatos; Axel Flinth; Ingo Roth; Giuseppe Caire (IEEE Trans. Wirel. Commun., 2019)

Hierarchical sparse recovery from hierarchically structured measurements. - Benedikt Groß; Axel Flinth; Ingo Roth; Jens Eisert; Gerhard Wunder (CoRR, 2020)

Reliable Recovery of Hierarchically Sparse Signals for Gaussian and Kronecker Product Measurements. - Ingo Roth; Martin Kliesch; Axel Flinth; Gerhard Wunder; Jens Eisert (IEEE Trans. Signal Process., 2020)

Hierarchical Sparse Recovery from Hierarchically Structured Measurements with Application to Massive Random Access. - Benedikt Groß; Axel Flinth; Ingo Roth; Jens Eisert; Gerhard Wunder (SSP, 2021)

Measure Concentration on the OFDM-Based Random Access Channel. - Gerhard Wunder; Axel Flinth; Benedikt Groß (SSP, 2021)

Hierarchical compressed sensing. - Jens Eisert; Axel Flinth; Benedikt Groß; Ingo Roth; Gerhard Wunder (CoRR, 2021)

Guaranteed blind deconvolution and demixing via hierarchically sparse reconstruction. - Axel Flinth; Ingo Roth; Benedikt Groß; Jens Eisert; Gerhard Wunder (CoRR, 2021)

On the linear convergence rates of exchange and continuous methods for total variation minimization. - Axel Flinth; Frédéric de Gournay; Pierre Weiss (Math. Program., 2021)

ZZ-Net: A Universal Rotation Equivariant Architecture for 2D Point Clouds. - Georg Bökman; Fredrik Kahl; Axel Flinth (CVPR, 2022)

In Search of Projectively Equivariant Neural Networks. - Georg Bökman; Axel Flinth; Fredrik Kahl (CoRR, 2022)

Bisparse Blind Deconvolution through Hierarchical Sparse Recovery. - Axel Flinth; Ingo Roth; Gerhard Wunder (CoRR, 2022)

Mimicking DH Key Exchange Over a Full Duplex Wireless Channel via Bisparse Blind Deconvolution. - Gerhard Wunder; Axel Flinth; Daniel Becker 011; Benedikt Groß (CommNet, 2023)

Rigidity Preserving Image Transformations and Equivariance in Perspective. - Lucas Brynte; Georg Bökman; Axel Flinth; Fredrik Kahl (SCIA (2), 2023)

Optimization Dynamics of Equivariant and Augmented Neural Networks. - Axel Flinth; Fredrik Ohlsson (CoRR, 2023)

In search of projectively equivariant networks. - Georg Bökman; Axel Flinth; Fredrik Kahl (Trans. Mach. Learn. Res., 2023)

One-Shot Messaging at Any Load Through Random Sub-Channeling in OFDM. - Gerhard Wunder; Axel Flinth; Benedikt Groß (IEEE Trans. Inf. Theory, 2023)

Perfectly Secure Key Agreement Over a Full Duplex Wireless Channel. - Gerhard Wunder; Axel Flinth; Daniel Becker 011; Benedikt Groß (CoRR, 2024)

Ensembles provably learn equivariance through data augmentation. - Oskar Nordenfors; Axel Flinth (CoRR, 2024)

Grid is Good. Adaptive Refinement Algorithms for Off-the-Grid Total Variation Minimization. - Axel Flinth; Frédéric de Gournay; Pierre Weiss (Open J. Math. Optim., 2025)

Optimization Dynamics of Equivariant and Augmented Neural Networks. - Oskar Nordenfors; Fredrik Ohlsson; Axel Flinth (Trans. Mach. Learn. Res., 2025)

Data Augmentation and Regularization for Learning Group Equivariance. - Oskar Nordenfors; Axel Flinth (CoRR, 2025)