Zobrazeno 1 - 10
of 334
pro vyhledávání: '"Hinton, P. E."'
The GLOM architecture proposed by Hinton [2021] is a recurrent neural network for parsing an image into a hierarchy of wholes and parts. When a part is ambiguous, GLOM assumes that the ambiguity can be resolved by allowing the part to make multi-moda
Externí odkaz:
http://arxiv.org/abs/2211.16564
Capsule networks aim to parse images into a hierarchy of objects, parts and relations. While promising, they remain limited by an inability to learn effective low level part descriptions. To address this issue we propose a way to learn primary capsul
Externí odkaz:
http://arxiv.org/abs/2011.13920
Objects are composed of a set of geometrically organized parts. We introduce an unsupervised capsule autoencoder (SCAE), which explicitly uses geometric relationships between parts to reason about objects. Since these relationships do not depend on t
Externí odkaz:
http://arxiv.org/abs/1906.06818
Autor:
Gomez, Aidan N., Zhang, Ivan, Kamalakara, Siddhartha Rao, Madaan, Divyam, Swersky, Kevin, Gal, Yarin, Hinton, Geoffrey E.
Neural networks are easier to optimise when they have many more weights than are required for modelling the mapping from inputs to outputs. This suggests a two-stage learning procedure that first learns a large net and then prunes away connections or
Externí odkaz:
http://arxiv.org/abs/1905.13678
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Bartunov, Sergey, Santoro, Adam, Richards, Blake A., Marris, Luke, Hinton, Geoffrey E., Lillicrap, Timothy
The backpropagation of error algorithm (BP) is impossible to implement in a real brain. The recent success of deep networks in machine learning and AI, however, has inspired proposals for understanding how the brain might learn across multiple layers
Externí odkaz:
http://arxiv.org/abs/1807.04587
Autor:
Anil, Rohan, Pereyra, Gabriel, Passos, Alexandre, Ormandi, Robert, Dahl, George E., Hinton, Geoffrey E.
Techniques such as ensembling and distillation promise model quality improvements when paired with almost any base model. However, due to increased test-time cost (for ensembles) and increased complexity of the training pipeline (for distillation), t
Externí odkaz:
http://arxiv.org/abs/1804.03235
A capsule is a group of neurons whose activity vector represents the instantiation parameters of a specific type of entity such as an object or an object part. We use the length of the activity vector to represent the probability that the entity exis
Externí odkaz:
http://arxiv.org/abs/1710.09829
Data are often labeled by many different experts with each expert only labeling a small fraction of the data and each data point being labeled by several experts. This reduces the workload on individual experts and also gives a better estimate of the
Externí odkaz:
http://arxiv.org/abs/1703.08774