2 citations · 3 across the 3 of their papers we have counts for
3 papers
Wormhole Loss for Partial Shape Matching
Amit Bracha, Thomas Dagès, Ron Kimmel
When matching parts of a surface to its whole, a fundamental question arises: Which points should be included in the matching process? The issue is intensified when using isometry…
A model is worth tens of thousands of examples
Thomas Dagès, Laurent D. Cohen, Alfred M. Bruckstein
Traditional signal processing methods relying on mathematical data generation models have been cast aside in favour of deep neural networks, which require vast amounts of data. Sin…
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
Neural networks are omnipresent, but remain poorly understood. Their increasing complexity and use in critical systems raises the important challenge to full interpretability. We p…