4 citations · 9 across the 11 of their papers we have counts for
5 papers · 1 filter
Point-to-set distance functions for weakly supervised segmentation
Bas Peters
When pixel-level masks or partial annotations are not available for training neural networks for semantic segmentation, it is possible to use higher-level information in the form o…
Deep connections between learning from limited labels & physical parameter estimation -- inspiration for regularization
Bas Peters
Recently established equivalences between differential equations and the structure of neural networks enabled some interpretation of training of a neural network as partial-differe…
Symmetric block-low-rank layers for fully reversible multilevel neural networks
Bas Peters, Eldad Haber, Keegan Lensink
Factors that limit the size of the input and output of a neural network include memory requirements for the network states/activations to compute gradients, as well as memory for t…
Fully Hyperbolic Convolutional Neural Networks
Keegan Lensink, Bas Peters, Eldad Haber
Convolutional Neural Networks (CNN) have recently seen tremendous success in various computer vision tasks. However, their application to problems with high dimensional input and o…
Automatic classification of geologic units in seismic images using partially interpreted examples
Bas Peters, Justin Granek, Eldad Haber
Geologic interpretation of large seismic stacked or migrated seismic images can be a time-consuming task for seismic interpreters. Neural network based semantic segmentation provid…