Thomas Dagès

According to our database, Thomas Dagès authored at least 17 papers between 2019 and 2026.

Collaborative distances:

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

2026

Generative Shape Reconstruction with Geometry-Guided Langevin Dynamics.

Linus Härenstam-Nielsen, Dmitrii Pozdeev, Thomas Dagès, Nikita Araslanov, Daniel Cremers

CoRR, March, 2026

Harnessing Data Asymmetry: Manifold Learning in the Finsler World.

Thomas Dagès, Simon Weber, Daniel Cremers, Ron Kimmel

CoRR, March, 2026

2025

Learning Eigenstructures of Unstructured Data Manifolds.

Roy Velich, Arkadi Piven, David Bensaïd, Daniel Cremers, Thomas Dagès, Ron Kimmel

CoRR, December, 2025

A model is worth tens of thousands of examples for estimation and thousands for classification.

Thomas Dagès, Laurent D. Cohen, Alfred M. Bruckstein

Pattern Recognit., 2025

Metric Convolutions: A Unifying Theory to Adaptive Image Convolutions.

Thomas Dagès, Michael Lindenbaum, Alfred M. Bruckstein

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding.

Thomas Dagès, Simon Weber, Ya-Wei Eileen Lin, Ronen Talmon, Daniel Cremers, Michael Lindenbaum, Alfred M. Bruckstein, Ron Kimmel

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

Metric Convolutions: A Unifying Theory to Adaptive Convolutions.

Thomas Dagès, Michael Lindenbaum, Alfred M. Bruckstein

CoRR, 2024

Wormhole Loss for Partial Shape Matching.

Amit Bracha, Thomas Dagès, Ron Kimmel

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Finsler-Laplace-Beltrami Operators with Application to Shape Analysis.

Simon Weber, Thomas Dagès, Maolin Gao, Daniel Cremers

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

On Unsupervised Partial Shape Correspondence.

Amit Bracha, Thomas Dagès, Ron Kimmel

Proceedings of the Computer Vision - ACCV 2024, 2024

2023

On Partial Shape Correspondence and Functional Maps.

Amit Bracha, Thomas Dagès, Ron Kimmel

CoRR, 2023

From Compass and Ruler to Convolution and Nonlinearity: On the Surprising Difficulty of Understanding a Simple CNN Solving a Simple Geometric Estimation Task.

Thomas Dagès, Michael Lindenbaum, Alfred M. Bruckstein

CoRR, 2023

A Model is Worth Tens of Thousands of Examples.

Thomas Dagès, Laurent D. Cohen, Alfred M. Bruckstein

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

2022

Doubly Stochastic Pairwise Interactions for Agreement and Alignment.

Thomas Dagès, Alfred M. Bruckstein

SIAM J. Appl. Math., 2022

2021

Probabilistic Gathering of Agents with Simple Sensors.

Ariel Barel, Thomas Dagès, Rotem Manor, Alfred M. Bruckstein

SIAM J. Appl. Math., 2021

A Bound on the Edge-Flipping Distance between Triangulations (Revisiting the Proof).

Thomas Dagès, Alfred M. Bruckstein

CoRR, 2021

2019

Seeing Things in Random-Dot Videos.

Thomas Dagès, Michael Lindenbaum, Alfred M. Bruckstein

Proceedings of the Pattern Recognition - 5th Asian Conference, 2019