David Belius

According to our database, David Belius authored at least 8 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression.

Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, David Belius

CoRR, 2024

Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum.

Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, David Belius

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Injectivity of ReLU networks: perspectives from statistical physics.

Antoine Maillard, Afonso S. Bandeira, David Belius, Ivan Dokmanic, Shuta Nakajima

CoRR, 2023

A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression.

Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, Ivan Dokmanic, David Belius

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Learning Multiscale Convolutional Dictionaries for Image Reconstruction.

Tianlin Liu, Anadi Chaman, David Belius, Ivan Dokmanic

IEEE Trans. Computational Imaging, 2022

Feature learning and random features in standard finite-width convolutional neural networks: An empirical study.

Maxim Samarin, Volker Roth, David Belius

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2020

Interpreting U-Nets via Task-Driven Multiscale Dictionary Learning.

Tianlin Liu, Anadi Chaman, David Belius, Ivan Dokmanic

CoRR, 2020

On the Empirical Neural Tangent Kernel of Standard Finite-Width Convolutional Neural Network Architectures.

Maxim Samarin, Volker Roth, David Belius

CoRR, 2020