Methods › General › Attention Mechanisms › Highway networks
Highway networks
Introduced by Rupesh Kumar Srivastava et al. in Highway Networks
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
There is plenty of theoretical and empirical evidence that depth of neural networks is a crucial ingredient for their success. However, network training becomes more difficult with increasing depth and training of very deep networks remains an open problem. In this extended abstract, we introduce a new architecture designed to ease gradient-based training of very deep networks. We refer to networks with this architecture as highway networks, since they allow unimpeded information flow across several layers on "information highways". The architecture is characterized by the use of gating units which learn to regulate the flow of information through a network. Highway networks with hundreds of layers can be trained directly using stochastic gradient descent and with a variety of activation functions, opening up the possibility of studying extremely deep and efficient architectures.
Papers archive 2025-07-28
24 shown of 24, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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To Stay or to Bypass: Unraveling Mainline Vehicles' Aggregate Strategic Decision-Making at Highway Weaving Ramps 13 May 2025 · 0 repositories · arXiv:2505.08965
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Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free 10 May 2025 · 1 repository · arXiv:2505.06708Syntology ran 3 of 3 samples · 0 unverified
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Deconstructing Recurrence, Attention, and Gating: Investigating the transferability of Transformers and Gated Recurrent Neural Networks in forecasting of dynamical systems 3 Oct 2024 · 0 repositories · arXiv:2410.02654
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Highway Networks for Improved Surface Reconstruction: The Role of Residuals and Weight Updates 11 Jul 2024 · 1 repository · arXiv:2407.08134
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Computer vision-based model for detecting turning lane features on Florida's public roadways 13 Jun 2024 · 0 repositories · arXiv:2406.08822
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Deep Learning-Based Vehicle Speed Prediction for Ecological Adaptive Cruise Control in Urban and Highway Scenarios 30 Nov 2022 · 0 repositories · arXiv:2212.00149
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Multi-task recommendation system for scientific papers with high-way networks 21 Apr 2022 · 0 repositories · arXiv:2204.09930
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Transfer Learning with Graph Neural Networks for Short-Term Highway Traffic Forecasting 17 Apr 2020 · 2 repositories · arXiv:2004.08038
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Graph-Partitioning-Based Diffusion Convolutional Recurrent Neural Network for Large-Scale Traffic Forecasting 24 Sep 2019 · 2 repositories · arXiv:1909.11197
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Investigating the effect of residual and highway connections in speech enhancement models 22 Oct 2018 · 1 repository
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Batch-normalized Recurrent Highway Networks 26 Sep 2018 · 1 repository · arXiv:1809.10271
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Semi-tied Units for Efficient Gating in LSTM and Highway Networks 18 Jun 2018 · 0 repositories · arXiv:1806.06513
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Humor Recognition Using Deep Learning 1 Jun 2018 · 0 repositories
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Avoiding degradation in deep feed-forward networks by phasing out skip-connections 1 Jan 2018 · 0 repositories
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Language Modeling with Recurrent Highway Hypernetworks 1 Dec 2017 · 0 repositories
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Exploiting Nontrivial Connectivity for Automatic Speech Recognition 28 Nov 2017 · 0 repositories · arXiv:1711.10271
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Lattice Recurrent Unit: Improving Convergence and Statistical Efficiency for Sequence Modeling 6 Oct 2017 · 3 repositories · arXiv:1710.02254
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Application of a Hybrid Bi-LSTM-CRF model to the task of Russian Named Entity Recognition 27 Sep 2017 · 2 repositories · arXiv:1709.09686
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Language Modeling with Highway LSTM 19 Sep 2017 · 0 repositories · arXiv:1709.06436
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Early Improving Recurrent Elastic Highway Network 14 Aug 2017 · 0 repositories · arXiv:1708.04116
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Faster Training of Very Deep Networks Via p-Norm Gates 11 Aug 2016 · 0 repositories · arXiv:1608.03639
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Choice by Elimination via Deep Neural Networks 17 Feb 2016 · 0 repositories · arXiv:1602.05285
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Training Very Deep Networks 22 Jul 2015 · 3 repositories · arXiv:1507.06228
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Highway Networks 3 May 2015 · 4 repositories · arXiv:1505.00387
Tasks archive 2025-07-28
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Usage over time archive 2025-07-28
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Categories archive 2025-07-28
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