Results 11 to 20 of about 3,951 (305)
Modeling Interval Timing by Recurrent Neural Nets [PDF]
Frontiers in Integrative Neuroscience, 2019 The purpose of this study was to take a new approach in showing how the central nervous system might encode time at the supra-second level using recurrent neural nets (RNNs).
Theodore Raphan +5 more
doaj +7 more sources
Multicategory choice modeling by recurrent neural nets [PDF]
Journal of Retailing and Consumer ServicesIn multicategory choice, a customer may purchase multiple products or product categories at the same time. Hidden variables of recurrent nets depend on current inputs and hidden variables of the previous period.
Harald Hruschka
exaly +4 more sources
Temporal codes and recurrent timing nets for rhythmic expectancy [PDF]
Frontiers in Computational NeuroscienceThis paper focuses on possible time-domain neurocomputational mechanisms for short-term anticipatory processes. Here we present a simple, signal processing functional model of how short-term rhythmic pattern expectancies could be computed on the fly ...
Peter Cariani +2 more
doaj +2 more sources
Evolutionary chromatographic law identification by recurrent neural nets
, 1995 Analytic chromatography is a physical process whose aim is the separation of the components of a chemical mixture, based on their different affinities for some porous medium through which they are percolated.
Alexandro Fadda, Marc Schoenauer
core +2 more sources
Learning temporal sequences in recurrent self-organising neural nets
, 1997 Learning temporal sequences in recurrent self-organising neural ...
Terry Caelli (13062708) +1 more
core +2 more sources
Automatic Synthesis of Neurons for Recurrent Neural Nets
CoRR, 2022 We present a new class of neurons, ARNs, which give a cross entropy on test data that is up to three times lower than the one achieved by carefully optimized LSTM neurons. The explanations for the huge improvements that often are achieved are elaborate skip connections through time, up to four internal memory states per neuron and a number of novel ...
Roland Olsson 0001 +2 more
openaire +2 more sources
Bayesian error propagation for neural-net based parameter inference
The Open Journal of Astrophysics, 2022 Neural nets have become popular to accelerate parameter inferences, especially for the upcoming generation of galaxy surveys in cosmology. As neural nets are approximative by nature, a recurrent question has been how to propagate the neural net's ...
Daniela Grandón, Elena Sellentin
doaj +1 more source
Sensors, 2021 Sea fog is a natural phenomenon that reduces the visibility of manned vehicles and vessels that rely on the visual interpretation of traffic. Fog clearance, also known as fog dissipation, is a relatively under-researched area when compared with fog ...
Jin Hyun Han +5 more
doaj +1 more source
Novel multi‐domain attention for abstractive summarisation
CAAI Transactions on Intelligence Technology, 2023 The existing abstractive text summarisation models only consider the word sequence correlations between the source document and the reference summary, and the summary generated by models lacks the cover of the subject of source document due to models ...
Chunxia Qu +4 more
doaj +1 more source
The Context-Dependent Additive Recurrent Neural Net [PDF]
Proceedings of the 2018 Conference of the North American Chapter of
the Association for Computational Linguistics: Human Language
Technologies, Volume 1 (Long Papers), 2018 Contextual sequence mapping is one of the fundamental problems in Natural Language Processing (NLP). Here, instead of relying solely on the information presented in the text, the learning agents have access to a strong external signal given to assist the learning process.
Quan Hung Tran +5 more
openaire +1 more source