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Response Characterization for Auditing Cell Dynamics in Long Short-term Memory Networks [article]

Ramin M. Hasani, Alexander Amini, Mathias Lechner, Felix Naser, Radu Grosu, Daniela Rus
2018 arXiv   pre-print
In this paper, we introduce a novel method to interpret recurrent neural networks (RNNs), particularly long short-term memory networks (LSTMs) at the cellular level.  ...  We propose a systematic pipeline for interpreting individual hidden state dynamics within the network using response characterization methods.  ...  Long Short-term Memory Long short term Memory (LSTM) (Hochreiter and Schmidhuber 1997) , are gated-recurrent neural networks architectures specifically designed to tackle the training challenges of RNNs  ... 
arXiv:1809.03864v1 fatcat:a5jg74y2yvhvvd5snsw2pw77me

Response Characterization for Auditing Cell Dynamics in Long Short-term Memory Networks

Ramin Hasani, Alexander Amini, Mathias Lechner, Felix Naser, Radu Grosu, Daniela Rus
2019 2019 International Joint Conference on Neural Networks (IJCNN)  
In this paper, we introduce a novel method to interpret recurrent neural networks (RNNs), particularly long short-term memory networks (LSTMs) at the cellular level.  ...  We propose a systematic pipeline for interpreting individual hidden state dynamics within the network using response characterization methods.  ...  Long Short-term Memory Long short term Memory (LSTM) (Hochreiter and Schmidhuber 1997) , are gated-recurrent neural networks architectures specifically designed to tackle the training challenges of RNNs  ... 
doi:10.1109/ijcnn.2019.8851954 dblp:conf/ijcnn/HasaniALNGR19 fatcat:xm6iqrc5tnhslisqvcfgde6xva

Identification and Early Warning of Financial Fraud Risk Based on Bidirectional Long-Short Term Memory Model

Xiaoli Liu, Min Fan
2022 Mathematical Problems in Engineering  
Then, the identification and early warning of financial fraud risk based on bidirectional long-short term memory model are proposed.  ...  companies and also for securities companies to accurately price related financial products of target companies.  ...  Bidirectional long-short term memory (LSTM) neural network model combines the advantages of bidirectional cyclic neural network model and short-long term memory neural network model.  ... 
doi:10.1155/2022/2342312 doaj:d30134ef26744120b2be03246e1cbfc3 fatcat:zypm6ztujnhllon3g5k4zvbcfi

The Correlation Theory of Brain Function [chapter]

Christoph von der Malsburg
1994 Models of Neural Networks  
Synaptic modulation and plasticity form the basis for short-term and long-term memory, respectively.  ...  Signal correlations, shaped by the variable network, express structure and relationships within objects. In particular, the gure-ground problem may be solved in this way.  ...  In short, the e ects of earlier correlations are stored in short-term memory.  ... 
doi:10.1007/978-1-4612-4320-5_2 fatcat:ulin7kft3rgfzniiduy73vnzea

A behavioral theory of insider-threat risks

Ignacio J. Martinez-Moyano, Eliot Rich, Stephen Conrad, David F. Andersen, Thomas R. Stewart
2008 ACM Transactions on Modeling and Computer Simulation  
Drawing on data related to information technology security violations and on a case study created to explain the dynamics observed in that data, the authors constructed a system dynamics model of a theory  ...  of the development of insider-threat risks and conducted numerical simulations to explore the parameter and response spaces of the model.  ...  The speed of the adjustment from short-term memory to long-term memory (α j ) and the speed for forgetting the contents of long-term memory (β j ) is thought to be proportional to the access the actors  ... 
doi:10.1145/1346325.1346328 fatcat:mifrvpzjv5ghdlsxhlmhijl7dq

How Do Living Systems Create Meaning?

Chris Fields, Michael Levin
2020 Philosophies  
Meaning has traditionally been regarded as a problem for philosophers and psychologists.  ...  Advances in cognitive science since the early 1960s, however, broadened discussions of meaning, or more technically, the semantics of perceptions, representations, and/or actions, into biology and computer  ...  Short-term memory for environmental state is implemented by receptor methylation [78] , while longer-term revision of expectations is implemented by modulating R 0 ; we discuss the roles of RFs as memories  ... 
doi:10.3390/philosophies5040036 fatcat:3fu6qr7sfrdelpuqc4bblhhlsa

Neuronal plasticity and antidepressant actions

Eero Castrén, René Hen
2013 Trends in Neurosciences  
amblyopia in adult humans.  ...  Acknowledgments The authors thank Sarah Mack for drawing Figure 1 Disclaimer statement E.C. is cofounder of and advisor to Hermo Pharma, which is running a clinical trial on the use of fluoxetine for  ...  A recent study reported that short-term glucocorticoid treatment increased spine dynamics in the mouse somatosensory cortex by simultaneously increasing spine formation and retraction, and that inhibition  ... 
doi:10.1016/j.tins.2012.12.010 pmid:23380665 pmcid:PMC3648595 fatcat:jhxm3uvmsbbkblgnendzp5l4sy

Pattern segmentation in a binary/analog world: unsupervised learning versus memory storing

C Lourenço, A Babloyantz, M Hougardy
2000 Neural Networks  
We extend the model by introducing a law of synaptic change, which allows the network to learn by structuring itself in response to stimuli with relevant features.  ...  We review their solution to the segmentation problem in associative memory, which consists in feature binding being expressed by synchrony relations between oscillators or populations of neurons.  ...  Short-term memory and memory recall are viewed as patterns of activity of the neural network.  ... 
doi:10.1016/s0893-6080(99)00087-8 pmid:10935461 fatcat:ph2dkc3l7zbaphac77dvbc4l7q

A spiking network model of short-term active memory

D Zipser, B Kehoe, G Littlewort, J Fuster
1993 Journal of Neuroscience  
[Key words: short-term memory, neural network model, inferotemporal cortex, memory model, spiking model neurons, attractor dynamics] Animals have memories with retention times ranging from fractions of  ...  Lesion and brain cooling studies have identified several cortical areas that are required for short-term memory tasks, such as delayed match to sample or delayed response, but not required for versions  ...  Cowan (1972) demonstrated attractor dynamics for recurrent networks of nonlinear units, and suggested that the fixed-point attractors might play a role in short-term memory.  ... 
doi:10.1523/jneurosci.13-08-03406.1993 pmid:8340815 fatcat:cwe4kmx2jbfznmucwt4pxhykhe

Effectiveness of Brainwave Synchronization in Alpha, Beta, and Theta Bands by Binaural Beats on Visuospatial Working Memory

2021 Avicenna Journal of Neuro Psycho Physiology  
All subjects were assessed in the pre-test and post-test stages by the Corsi blocks tapping test. Participants in the experimental groups received 15, 9, 5, and 6 Hz binaural beats for 12 min.  ...  Conclusions: Given that working memory is the basis of numerous cognitive functions, using 15 Hz binaural beats could improve the visuospatial working memory in these people  ...  There are several classifications for memory, including sensory, short-term, and long-term memory. In recent decades, the term of working memory has replaced short-term memory.  ... 
doi:10.32592/ajnpp.2021.8.4.103 fatcat:7oym3bijtvc2zigzc5i7zrukj4

Design and Application of Intelligent Financial Accounting Model Based on Knowledge Graph

Xuechen Hou
2022 Mobile Information Systems  
With the continuous progress of science and technology, economic globalization has become an important direction for the development of enterprises.  ...  In the process of enterprise development, artificial intelligence and machine learning techniques have greatly improved the efficiency of enterprise accounting and financial management and have gradually  ...  deals with sequential data, and the forward calculation process of long short-term memory (LSTM) network can be expressed as equations ( 1 )-( 5 ). e cell structure of LSTM is shown in Figure 3 .  ... 
doi:10.1155/2022/8353937 doaj:d9df63601f444490b1f6e47a476e1891 fatcat:w7rvj26uyba47pwmidv7ie7te4

Pattern Segmentation in Associative Memory

DeLiang Wang, Joachim Buhmann, Christoph von der Malsburg
1990 Neural Computation  
The goal of this paper is to show how to modify associative memory such that it can discriminate several stored patterns in a composite input and represent them simultaneously.  ...  In our simulations, temporal patterns take the form of oscillatory bursts of activity. Model oscillators consist of pairs of local cell populations connected appropriately.  ...  Since in this formulation short-term memory states are dynamic attractor states, one speaks of attractor neural networks.  ... 
doi:10.1162/neco.1990.2.1.94 fatcat:rfasn3nu55e3zb332iakrsvqge

Odor representations in the olfactory bulb evolve after the first breath and persist as an odor afterimage

M. A. Patterson, S. Lagier, A. Carleton
2013 Proceedings of the National Academy of Sciences of the United States of America  
In conclusion, we have found that the odor response is dynamic and that one must consider all breaths of the response during an odor and afterward to characterize a cell's "odor receptive field."  ...  These dynamics may help identify novel odorants in complex environments. multielectrode recording | network dynamics | optogenetics S ensory systems, even when presented with fixed stimuli, use dynamic  ...  We are grateful to Anthony Holtmaat for providing Thy1-ChR2 mice and to Richard Benton for technical assistance with the miniPID.  ... 
doi:10.1073/pnas.1303873110 pmid:23918364 pmcid:PMC3761593 fatcat:7ns6mn76obhiletfdxdymteae4

A Dynamic DL-driven architecture to Combat Sophisticated Android Malware

Iram Bibi, Adnan Akhunzada, Jahanzaib Malik, Javed Iqbal, Arslan Musaddiq, Sung Won Kim
2020 IEEE Access  
INDEX TERMS Android malware, deep learning, recurrent neural network, convolutional neural network, deep neural network, mobile security. 129600 This work is licensed under a Creative Commons Attribution  ...  The predominant Android operating system has captured enormous attention globally not only in smart phone industry but also for varied smart devices.  ...  Moreover, Long short-term memory (LSTM) in [24] is employed for malware characterization in Android.  ... 
doi:10.1109/access.2020.3009819 fatcat:42ezsnhtbfddll6g2z5ex4fhcy

Neural dynamics of speech and language coding: developmental programs, perceptual grouping, and competition for short-term memory

M Cohen, S Grossberg
1986 Human neurobiology  
Within these networks, a spatial frequency analysis of temporally evolving activity patterns leads to competitive masking of inappropriate list encodings in short term memory.  ...  Several design principles are embodied by the networks, such as the sequence masking principle, the long-term memory invariance principle, and the principle of self-similar growth.  ...  Psychol Rev (in press) Grossberg S, Stone GO (1986b) Neural dynamics of attention switch¬ ing and temporal order information in short term memory.  ... 
pmid:3516940 fatcat:7t4aamtbe5e6dizhbx2o3tripq
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