no code implementations • 29 Sep 2021 • Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael Curtis Mozer
We propose a method, Head-to-Toe probing (Head2Toe), that selects features from all layers of the source model to train a classification head for the target-domain.
no code implementations • NeurIPS 2021 • Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio
Deep learning has advanced from fully connected architectures to structured models organized into components, e. g., the transformer composed of positional elements, modular architectures divided into slots, and graph neural nets made up of nodes.
no code implementations • 1 Jan 2021 • Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Bernhard Schölkopf, Michael Curtis Mozer, Hugo Larochelle, Christopher Pal, Yoshua Bengio
Promising results have driven a recent surge of interest in continuous optimization methods for Bayesian network structure learning from observational data.
no code implementations • ICLR 2021 • Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Michael Curtis Mozer
To use a video game as an illustration, two enemies of the same type will share schemata but will have separate object files to encode their distinct state (e. g., health, position).
no code implementations • NeurIPS Workshop SVRHM 2020 • Ioanna Maria Attarian, Brett D Roads, Michael Curtis Mozer
Deep-learning vision models have shown intriguing similarities and differences with respect to human vision.