on Pattern Analysis and Machine Intelligence

By J. Macho, E. Costa, Régis Vaillant, L. Launay, Y. Trousset, R. Romeas. 2005

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Deep Kalman Filters (2015, methodology): “Models that rely on predicting the next image based on the previous one (Goroshin et al. , 2015; Memisevic, 2013) may not sufﬁce to learn the structure of digits in the presence of large noise and rotation.”
End-to-End Text Recognition with Hybrid HMM Maxout Models (2013, methodology): “HMMs have long been among the main tools used for sequence modelling in voice recognition (Rabiner, 1989) and hand-writing recognition (Hu et al., 1996).”
3D Scene Flow Estimation with a Piecewise Rigid Scene Model (2015, methodology): “While progress in dense binocular stereo (Bleyer et al. 2011b; Hirschmüller 2008; Yamaguchi et al. 2012, etc.) and optical ﬂow (Brox et al. 2004; Sun et al. 2010; Unger et al. 2012, among others) has been both steady and signiﬁcant over the years, the performance of 3D scene ﬂow algorithms (e.g.,…”
Quantum Principal Component Analysis (2015, methodology): “Examples of PCA with different descriptions and settings include probabilistic PCA [3], nonlinear PCA [4], kernel PCA [5] as a nonlinear extension of PCA, local PCA [6] for dimension reduction, and generalized PCA [7], applied to a wide variety of problems in science and engineering [2]: e.”