Results 51 to 60 of about 92,175 (266)

Dilated Recurrent Neural Networks

CoRR, 2017
Learning with recurrent neural networks (RNNs) on long sequences is a notoriously difficult task. There are three major challenges: 1) complex dependencies, 2) vanishing and exploding gradients, and 3) efficient parallelization. In this paper, we introduce a simple yet effective RNN connection structure, the DilatedRNN, which simultaneously tackles all
Shiyu Chang, Yang Zhang 0001, Wei Han 0002, Mo Yu, Xiaoxiao Guo, Wei Tan 0001, Xiaodong Cui, Michael Witbrock, Mark Hasegawa-Johnson, Thomas S. Huang   +9 more
openaire   +3 more sources

Evaluation of the Performance of Feedforward and Recurrent Neural Networks in Active Cancellation of Sound Noise [PDF]

Journal of Intelligent Procedures in Electrical Technology, 2012
Active noise control is based on the destructive interference between the primary noise and generated noise from the secondary source. An antinoise of equal amplitude and opposite phase is generated and combined with the primary noise.
Mehrshad Salmasi, Homayoun Mahdavi-Nasab
doaj  

Segmental Recurrent Neural Networks

, 2015
We introduce segmental recurrent neural networks (SRNNs) which define, given an input sequence, a joint probability distribution over segmentations of the input and labelings of the segments. Representations of the input segments (i.e., contiguous subsequences of the input) are computed by encoding their constituent tokens using bidirectional recurrent
Lingpeng Kong, Chris Dyer, Noah A. Smith
openaire   +2 more sources

Linked Recurrent Neural Networks

CoRR, 2018
Recurrent Neural Networks (RNNs) have been proven to be effective in modeling sequential data and they have been applied to boost a variety of tasks such as document classification, speech recognition and machine translation. Most of existing RNN models have been designed for sequences assumed to be identically and independently distributed (i.i.d ...
Zhiwei Wang 0001, Yao Ma 0001, Dawei Yin 0001, Jiliang Tang   +3 more
openaire   +2 more sources

An Improved Recurrent Neural Network for Industrial IoT Botnet Attack Detection

Журнал інженерних наук
This research aims to improve the Industrial Internet of Things (IIoT) security, which fosters technological confidence and promotes expansion. The IIoT is mainly used in manufacturing, oil, and gas to avoid botnet attacks.
G. Suneetha, D.H. Priya
doaj   +1 more source

Forecasting the Cumulative COVID-19 Cases in Indonesia Using Flower Pollination Algorithm

Computation, 2022
Coronavirus disease 2019 (COVID-19) was declared as a global pandemic by the World Health Organization (WHO) on 12 March 2020. Indonesia is reported to have the highest number of cases in Southeast Asia.
Afiahayati, Yap Bee Wah, Sri Hartati, Yunita Sari, I Nyoman Prayana Trisna, Diyah Utami Kusumaning Putri, Aina Musdholifah, Retantyo Wardoyo   +7 more
doaj   +1 more source

Grounded Recurrent Neural Networks

CoRR, 2017
In this work, we present the Grounded Recurrent Neural Network (GRNN), a recurrent neural network architecture for multi-label prediction which explicitly ties labels to specific dimensions of the recurrent hidden state (we call this process "grounding"). The approach is particularly well-suited for extracting large numbers of concepts from text.
Ankit Vani, Yacine Jernite, David A. Sontag   +2 more
openaire   +2 more sources

Reciprocal control of viral infection and phosphoinositide dynamics

FEBS Letters, EarlyView.
Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley   +1 more source

Multistability in Recurrent Neural Networks [PDF]

SIAM Journal on Applied Mathematics, 2006
Stable stationary solutions correspond to memory capacity in the application of associative memory for neural networks. In this presentation, existence of multiple stable stationary solutions for Hopfield-type neural networks with delay and without delay is investigated. Basins of attraction for these stationary solutions are also estimated.
Chang-Yuan Cheng, Kuang-Hui Lin, Chih-Wen Shih   +2 more
openaire   +1 more source

Organ‐specific redox imbalances in spinal muscular atrophy mice are partially rescued by SMN antisense oligonucleotides

FEBS Letters, EarlyView.
We identified a systemic, progressive loss of protein S‐glutathionylation—detected by nonreducing western blotting—alongside dysregulation of glutathione‐cycle enzymes in both neuronal and peripheral tissues of Taiwanese SMA mice. These alterations were partially rescued by SMN antisense oligonucleotide therapy, revealing persistent redox imbalance as ...
Sofia Vrettou, Brunhilde Wirth
wiley   +1 more source