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Backpropagation through time
Known as:
BPTT
Backpropagation through time (BPTT) is a gradient-based technique for training certain types of recurrent neural networks. It can be used to train…
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Related topics
Related topics
8 relations
Backpropagation
Backpropagation through structure
Evolutionary programming
Gradient
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Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2020
2020
Word Interdependence Exposes How LSTMs Compose Representations
Naomi Saphra
,
Adam Lopez
arXiv.org
2020
Corpus ID: 216562291
Recent work in NLP shows that LSTM language models capture compositional structure in language data. For a closer look at how…
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2016
2016
A Visual and Textual Recurrent Neural Network for Sequential Prediction
Qiang Cui
,
Shu Wu
,
Q. Liu
,
Liang Wang
arXiv.org
2016
Corpus ID: 16354532
Sequential prediction is a fundamental task for Web applications. Due to the insufficiency of user feedbacks, sequential…
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2013
2013
Memetic cooperative coevolution of Elman recurrent neural networks
Rohitash Chandra
Soft Computing - A Fusion of Foundations…
2013
Corpus ID: 15247816
Cooperative coevolution decomposes an optimisation problem into subcomponents and collectively solves them using evolutionary…
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2006
2006
GAUSSIAN MIXTURE MODEL BASED SYSTEM IDENTIFICATION AND CONTROL
J. Lan
2006
Corpus ID: 124529077
of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the…
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2006
2006
Development of A New Recurrent Neural Network Toolbox (RNN-Tool) ⁄
Le Yang
,
Yanbo Xue
2006
Corpus ID: 14200657
In this report, we developed a new recurrent neural network toolbox, including the recurrent multilayer perceptron structure and…
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2003
2003
HYBRID TRAJECTORY PLANNING USING REINFORCEMENT AND BACKPROPAGATION THROUGH TIME TECHNIQUES
A. Nuseirat
,
R. A. Zitar
Cybernetics and systems
2003
Corpus ID: 23226269
A novel approach for trajectory planning of a mobile robot is presented. The mobile robot is assumed to move in a two-dimensional…
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2003
2003
Prediction of the Number of Residue Contacts in Proteins using LSTM Neural Networks
A. Jacobsson
,
Christian Gustavsson
2003
Corpus ID: 60313914
III Abstract In this thesis a relatively new neural network based predictor, LSTM (Long ShortTerm Memory), has been tested on the…
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2001
2001
A Neural Abstract Machine
E. Börger
,
Diego Sona
Journal of universal computer science (Online)
2001
Corpus ID: 7410972
In an attempt to capture the fundamental features that are common to neural networks, we define a parameterized Neural Abstract…
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1997
1997
Applying Backpropagation through Time to a Real Inverted Pendulum Problem
E. Pasero
,
M. Costa
,
F. Palma
,
D. Palmisano
1997
Corpus ID: 16261302
The “inverted pendulum problem” is perhaps the most widely used benchmarking study to assess the effectiveness of emerging…
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1993
1993
Phase-Space Learning for Recurrent Networks
Fu-Sheng Tsung
,
G. Cottrell
1993
Corpus ID: 14243802
We study the problem of learning nonstatic attractors in recurrent networks. With concepts from dynamical systems theory, we show…
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