104 citations · 673 across the 47 of their papers we have counts for
4 papers · 1 filter
Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching
Stepan Tulyakov, Anton Ivanov, Francois Fleuret
End-to-end deep-learning networks recently demonstrated extremely good perfor- mance for stereo matching. However, existing networks are difficult to use for practical applications…
Not All Samples Are Created Equal: Deep Learning with Importance Sampling
Angelos Katharopoulos, François Fleuret
Deep neural network training spends most of the computation on examples that are properly handled, and could be ignored. We propose to mitigate this phenomenon with a principled im…
Knowledge Transfer with Jacobian Matching
Suraj Srinivas, Francois Fleuret
Classical distillation methods transfer representations from a "teacher" neural network to a "student" network by matching their output activations. Recent methods also match the J…
Geodesic Convolutional Shape Optimization
Pierre Baqué, Edoardo Remelli, François Fleuret +1
Aerodynamic shape optimization has many industrial applications. Existing methods, however, are so computationally demanding that typical engineering practices are to either simply…