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Feb 13, 2018 · Review: The paper proposes a method to encode and decode symbolic representations in vectors using neural networks. This is a very important problem in neural ...
Mar 10, 2018 · We present a formal language with expressions denoting general symbol structures and queries which access information in those structures. A ...
In general, DNNs may be expected to benefit if they can incorporate some of the power of symbolic computation without compromising the power of deep learning.
A formal language with expressions denoting general symbol structures and queries which access information in those structures is presented, which shares a ...
Learning and Analyzing Vector Encoding of Symbolic ... - dblp
dblp.org › conf › iclr › FernandezCSS18
Roland Fernandez, Asli Celikyilmaz, Paul Smolensky, Rishabh Singh: Learning and Analyzing Vector Encoding of Symbolic Representation. ICLR (Workshop) 2018.
Learning and Analyzing Vector Encoding of Symbolic Representation. Roland Fernandez, Asli Çelikyilmaz, Paul Smolensky, Rishabh Singh.
We present a formal language with expressions denoting general symbol structures and queries which access information in those structures. A
Recurrent neural networks (RNNs) can learn continuous vector representations of symbolic structures such as sequences and sentences; these representations often ...
Learning and Analyzing Vector Encoding of Symbolic Representation. Roland Fernandez Asli Celikyilmaz Paul Smolensky Rishabh Singh.
Learning and analyzing vector encoding of symbolic representations · Roland Fernandez, Asli Celikyilmaz, Rishabh Singh, Paul Smolensky. ICLR 2018 | March 2018.