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Neural Associative Memory for Dual-Sequence Modeling [article]

Dirk Weissenborn
2016 arXiv   pre-print
In this work we propose a new architecture for dual-sequence modeling that is based on associative memory.  ...  We derive AM-RNNs, a recurrent associative memory (AM) which augments generic recurrent neural networks (RNN). This architecture is extended to the Dual AM-RNN which operates on two AMs at once.  ...  Acknowledgments We thank Sebastian Krause, Tim Rocktäschel and Leonhard Hennig for comments on an early draft of this work.  ... 
arXiv:1606.03864v2 fatcat:udc76ezugjcozktjs7llsbpq6a

Neural Associative Memory for Dual-Sequence Modeling

Dirk Weissenborn
2016 Proceedings of the 1st Workshop on Representation Learning for NLP  
In this work we propose a new architecture for dual-sequence modeling that is based on associative memory.  ...  We derive AM-RNNs, a recurrent associative memory (AM) which augments generic recurrent neural networks (RNN). This architecture is extended to the Dual AM-RNN which operates on two AMs at once.  ...  Acknowledgments We thank Sebastian Krause, Tim Rocktäschel and Leonhard Hennig for comments on an early draft of this work.  ... 
doi:10.18653/v1/w16-1630 dblp:conf/rep4nlp/Weissenborn16 fatcat:7ii2on72bfh6pp7owiojf4xvhi

Dual-Network Memory Model For Temporal Sequences

Motonobu Hattori, Rina Suzuki
2014 Zenodo  
We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns.  ...  The computer simulation results show the effectiveness of the proposed dual-network memory model.  ...  NOVEL DUAL-NETWORK MEMORY MODEL FOR TEMPORAL SEQUENCES Fig. 2 shows the structure of the proposed dual-network memory model.  ... 
doi:10.5281/zenodo.1336104 fatcat:5k7isd2qafh4lmummkemenbwzq

Research on Ship Motion Prediction Algorithm Based on Dual-pass Long Short-Term Memory Neural Network

Xiong Hu, Boyi Zhang, Gang Tang
2021 IEEE Access  
In response to this problem, a novel type of dual-pass Long Short-Term Memory (LSTM) neural network architecture is developed, on the basis of regular LSTM neural network.  ...  INDEX TERMS Dual-pass LSTM neural network, generalized autoregressive conditional heteroskedasticity (GARCH) model, inertial navigation system (INS).  ...  GARCH MODEL AND DUAL-PASS LSTM NEURAL NETWORK APPROXIMATION Generalized conditional heteroscedasticity (GARCH) is an autoregressive conditional heteroscedasticity model for the variance of time series  ... 
doi:10.1109/access.2021.3055253 fatcat:3nuscmei7veybcxvmqxjd7fgue

Lifelong Learning of Spatiotemporal Representations with Dual-Memory Recurrent Self-Organization [article]

German I. Parisi, Jun Tani, Cornelius Weber, Stefan Wermter
2018 Frontiers in Neurorobotics   accepted
In this paper, we propose a dual-memory self-organizing architecture for lifelong learning scenarios.  ...  For the consolidation of knowledge in the absence of external sensory input, the episodic memory periodically replays trajectories of neural reactivations.  ...  The authors would like to thank Pablo Barros and Vadym Gryshchuk for technical support.  ... 
doi:10.3389/fnbot.2018.00078 pmid:30546302 pmcid:PMC6279894 arXiv:1805.10966v4 fatcat:ou5sjdf6gbfzrjx5vojuyrnuca

DeepProcess: Supporting business process execution using a MANN-based recommender system [article]

Asjad Khan, Hung Le, Kien Do, Truyen Tran, Aditya Ghose, Hoa Dam, Renuka Sindhgatta
2021 arXiv   pre-print
We propose a novel network architecture, namely Write-Protected Dual Controller Memory-Augmented Neural Network (DCw-MANN), for building prescriptive models.  ...  Based on recent advances in the field of deep learning, we present a novel memory-augmented neural network (MANN) based approach for constructing a process-aware recommender system.  ...  Fig. 1 . 1 Recurrent Neural Network and Long Short Term Memory Fig. 2 . 2 The internal structure of LSTM Fig. 3 . 3 Write-Protected Dual Controller Memory Augmented Neural Network Model operations  ... 
arXiv:1802.00938v2 fatcat:3besbszopnetljtk4553iet5gq

Memory and attention in deep learning [article]

Hung Le
2021 arXiv   pre-print
Turing Machine via Neural Stored-program Memory-a new kind of external memory for neural networks.  ...  Its contributions include: (i) presenting a collection of taxonomies for memory, (ii) constructing new memory-augmented neural networks (MANNs) that support multiple control and memory units, (iii) introducing  ...  our first contributions: Dual Controller Write-Protected Memory Augmented Neural Network (DCw-MANN), an extension of MANN to model sequence to sequence mapping, and Dual Memory Neural Computer (DMNC)  ... 
arXiv:2107.01390v1 fatcat:nxxjns7qdfb2fhe53qwwylagui

Dual coding in an auto-associative network model of the hippocampus

Daniel Bush, Andrew Philippides, Phil Husbands, Michael O'Shea
2009 BMC Neuroscience  
Here we present a novel spiking neural network model which is, to our knowledge, the first to use a dual coding system in order to learn and recall associations between both temporally coded (spatial)  ...  Methods The postulated function of the hippocampus in spatial and episodic memory has been widely and successfully modelled using auto-associative networks [6] .  ... 
doi:10.1186/1471-2202-10-s1-o7 fatcat:bsztrs363nd6dndx5mrg52rvxq

Dual Coding in an Auto-associative Network Model of the Hippocampus

O-Shea Michael
2009 Frontiers in Computational Neuroscience  
Here we present a novel spiking neural network model which is, to our knowledge, the first to use a dual coding system in order to learn and recall associations between both temporally coded (spatial)  ...  Methods The postulated function of the hippocampus in spatial and episodic memory has been widely and successfully modelled using auto-associative networks [6] .  ... 
doi:10.3389/conf.neuro.10.2009.14.094 fatcat:pq52belhk5f5tidzmcmaj4yqjm

A cognitive framework for explaining serial processing and sequence execution strategies

Willem B. Verwey, Charles H. Shea, David L. Wright
2014 Psychonomic Bulletin & Review  
We argue that C-SMB accounts for cognitive models developed for a range of sequential motor tasks (like those proposed by Keele et al.).  ...  On the basis of this framework, we present a classification of the sequence execution strategies that helps researchers to better understand the cognitive and neural underpinnings of serial movement behavior  ...  In conclusion, studies with discrete keying sequences have been explained by the Dual Processor Model (Verwey, 2001) . Like the Dual Processor Model, C-SMB can account for discrete keying sequences.  ... 
doi:10.3758/s13423-014-0773-4 pmid:25421407 fatcat:zk5zxvhgfnewdeb65vfrdkh7o4

Within the framework of the dual-system model, voluntary action is central to cognition

Arnold L. Glass
2019 Attention, Perception & Psychophysics  
However, unlike in previous dual-system models, human cognitive activity involved in task performance is not exclusively associated with one system or the other.  ...  Furthermore, within the model, the computational competencies of the two systems are used to construct purposeful sequences of actions-that is, skills.  ...  Comparison with earlier dual-system models In earlier versions of the dual-system model, the habit system was associated solely with procedural learning and implicit effects on performance.  ... 
doi:10.3758/s13414-019-01737-0 pmid:31062301 fatcat:55djnjfjefdsrdw7pp4zdlog6a

Adaptive Value Normalization in the Prefrontal Cortex Is Reduced by Memory Load

L. Holper, L. D. Van Brussel, L. Schmidt, S. Schulthess, C. J. Burke, K. Louie, E. Seifritz, P. N. Tobler
2017 eNeuro  
Formal model comparison showed that a divisive normalization model fitted effects of both risk context and working memory demands on PFC activity better than alternative models of value adaptation, and  ...  Adaptation facilitates neural representation of a wide range of diverse inputs, including reward values.  ...  Acknowledgments: We thank all participants for participation.  ... 
doi:10.1523/eneuro.0365-17.2017 pmid:28462394 pmcid:PMC5409984 fatcat:2dkov2rnsjhexchgi5iiw3h2xe

Page 3408 of Psychological Abstracts Vol. 92, Issue 10 [page]

2005 Psychological Abstracts  
Implications for dual-process mod- els of memory in old age are discussed. —Journal abstract 28323. Hoffman, Joachim & Sebald, Albrecht.  ...  (De- partment of Psychology, Claremont Graduate University, CA) Dual-Pro- cess Models of Associative Recognition in Young and Older Adults: Evidence From Receiver Operating Characteristics.  ... 

Dissociable neural systems of sequence learning

Freja Gheysen, Wim Fias
2012 Advances in Cognitive Psychology  
sequence learning, neural systems, hippocampus, basal ganglia, serial reaction time task, artificial grammar task Although current theories all point to distinct neural systems for sequence learning, no  ...  reviews these two distinctions, yet concludes that these traditional dichotomies prove insufficient to account for all data on sequence learning and its neural organization. instead, a broader theoretical  ...  Ultimately, this model is of great interest since it highly relates with general principles of associative learning and memory (O'Reilly & Rudy, 2001) .  ... 
doi:10.5709/acp-0105-1 fatcat:kkzrphsu7jhgrijqz2dqsoy3pm

Dissociable neural systems of sequence learning

Freja Gheysen, Wim Fias
2012 Advances in Cognitive Psychology  
Although current theories all point to distinct neural systems for sequence learning, no consensus has been reached on which factors crucially define this distinction.  ...  This paper reviews these two distinctions, yet concludes that these traditional dichotomies prove insufficient to account for all data on sequence learning and its neural organization.  ...  Ultimately, this model is of great interest since it highly relates with general principles of associative learning and memory (O'Reilly & Rudy, 2001) .  ... 
doi:10.2478/v10053-008-0105-1 pmid:22679463 pmcid:PMC3367868 fatcat:jvwmof3ni5ffvdnu6bglioi4ee
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