Results 31 to 40 of about 2,867,003 (376)
Preregistered Replication of the Auditory Deviant Effect: A Robust Benchmark Finding
Journal of Cognition, 2019 Short-term memory of visually presented lists of items is disrupted by auditory distraction. The auditory deviant effect refers to the finding that a sequence in which a single auditory event deviates from all other auditory objects disrupts serial ...
Raoul Bell +4 more
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Rainfall–runoff modelling using Long Short-Term Memory (LSTM) networks
Hydrology and Earth System Sciences, 2018 . Rainfall–runoff modelling is one of the key challenges in the field of hydrology. Various approaches exist, ranging from physically based over conceptual to fully data-driven models.
Frederik Kratzert +4 more
semanticscholar +1 more source
Deep Sentence Embedding Using Long Short-Term Memory Networks: Analysis and Application to Information Retrieval [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2015 This paper develops a model that addresses sentence embedding, a hot topic in current natural language processing research, using recurrent neural networks (RNN) with Long Short-Term Memory (LSTM) cells.
Hamid Palangi +7 more
semanticscholar +1 more source
Fluctuations of Attention and Working Memory
Journal of Cognition, 2019 Attention and working memory are intricately related, yet there remain ambiguities in how to best characterize this relationship. In his review, Oberauer formalizes several dimensions for the relationship between attention and working memory, focusing ...
Kirsten C.S. Adam +1 more
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Sensors, 2022 Short-term load forecasting is viewed as one promising technology for demand prediction under the most critical inputs for the promising arrangement of power plant units.
Lichao Sun +4 more
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Frontiers in Human Neuroscience, 2015 Performance on working memory (WM) tasks may partially be supported by long-term memory (LTM) processing. Hence, brain activation recently being implicated in WM may actually have been driven by (incidental) LTM formation. We examined which brain regions
Heiko eBergmann +6 more
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PLoS ONE, 2017 The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long ...
Wei Bao, Jun Yue, Yulei Rao
semanticscholar +1 more source
Transition-Based Dependency Parsing with Stack Long Short-Term Memory [PDF]
Annual Meeting of the Association for Computational Linguistics, 2015 This work was sponsored in part by the U. S. Army Research Laboratory and the U. S. Army Research Office/nunder contract/grant number W911NF-10-1-0533, and in part by NSF CAREER grant IIS-1054319./nMiguel Ballesteros is supported by the European ...
Chris Dyer +4 more
semanticscholar +1 more source
Frontiers in Pharmacology, 2017 This review aims to classify and clarify, from a neuroanatomical, neurophysiological, and psychological perspective, different memory models that are currently widespread in the literature as well as to describe their origins.
Eduardo Camina +2 more
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A Short Review About Working Memory
Ankara Üniversitesi Tıp Fakültesi Mecmuas, 2021 The working memory system is responsible for the protection of limited information that can be kept in mind at once. Discussions on the existence of different circuits for different working memory, the limit of working memory and its developability are ...
Evrim Gökçe +2 more
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