On the Empirical Neural Tangent Kernel of Standard Finite-Width Convolutional Neural Network Architectures. - Maxim Samarin; Volker Roth 001; David Belius (CoRR, 2020)

Interpreting U-Nets via Task-Driven Multiscale Dictionary Learning. - Tianlin Liu; Anadi Chaman; David Belius; Ivan Dokmanic (CoRR, 2020)

Feature learning and random features in standard finite-width convolutional neural networks: An empirical study. - Maxim Samarin; Volker Roth 001; David Belius (UAI, 2022)

Learning Multiscale Convolutional Dictionaries for Image Reconstruction. - Tianlin Liu; Anadi Chaman; David Belius; Ivan Dokmanic (IEEE Trans. Computational Imaging, 2022)

A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression. - Tin Sum Cheng; Aurélien Lucchi; Anastasis Kratsios; Ivan Dokmanic; David Belius (NeurIPS, 2023)

Injectivity of ReLU networks: perspectives from statistical physics. - Antoine Maillard; Afonso S. Bandeira; David Belius; Ivan Dokmanic; Shuta Nakajima (CoRR, 2023)

Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum. - Tin Sum Cheng; Aurélien Lucchi; Anastasis Kratsios; David Belius (ICML, 2024)

A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression. - Tin Sum Cheng; Aurélien Lucchi; Anastasis Kratsios; David Belius (NeurIPS, 2024)

A thorough reproduction and evaluation of µP. - Georgios Vlassis; David Belius; Volodymyr Fomichov (Trans. Mach. Learn. Res., 2025)