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» Learning Precise Timing with LSTM Recurrent Networks
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IROS
2006
IEEE
126views Robotics» more  IROS 2006»
13 years 11 months ago
A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks
Abstract— Tying suture knots is a time-consuming task performed frequently during Minimally Invasive Surgery (MIS). Automating this task could greatly reduce total surgery time f...
Hermann Georg Mayer, Faustino J. Gomez, Daan Wiers...
ICANN
2005
Springer
13 years 10 months ago
Classifying Unprompted Speech by Retraining LSTM Nets
Abstract. We apply Long Short-Term Memory (LSTM) recurrent neural networks to a large corpus of unprompted speech- the German part of the VERBMOBIL corpus. Training first on a fra...
Nicole Beringer, Alex Graves, Florian Schiel, J&uu...
ICASSP
2009
IEEE
13 years 12 months ago
Robust discriminative keyword spotting for emotionally colored spontaneous speech using bidirectional LSTM networks
In this paper we propose a new technique for robust keyword spotting that uses bidirectional Long Short-Term Memory (BLSTM) recurrent neural nets to incorporate contextual informa...
Martin Wöllmer, Florian Eyben, Joseph Keshet,...
JMLR
2010
227views more  JMLR 2010»
13 years 3 months ago
PyBrain
PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easyto-use yet still powerful algorithms for machine learning tasks, including a vari...
Tom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, M...
NECO
2008
156views more  NECO 2008»
13 years 5 months ago
Dynamical Constraints on Using Precise Spike Timing to Compute in Recurrent Cortical Networks
ns. We have previously developed an abstract dynamical system for networks of spiking neurons that has allowed us to identify the criterion for the stationary dynamics of a network...
Arunava Banerjee, Peggy Seriès, Alexandre P...