Methods › General › Activation Functions › Maxout
Maxout
Introduced by Ian J. Goodfellow et al. in Maxout Networks
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
The Maxout Unit is a generalization of the ReLU and the leaky ReLU functions. It is a piecewise linear function that returns the maximum of the inputs, designed to be used in conjunction with dropout. Both ReLU and leaky ReLU are special cases of Maxout.
f(x) = max(wᵀ₁x + b₁, wᵀ₂x + b₂)
The main drawback of Maxout is that it is computationally expensive as it doubles the number of parameters for each neuron.
Papers archive 2025-07-28
30 shown of 50, 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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Deep-ICE: The first globally optimal algorithm for empirical risk minimization of two-layer maxout and ReLU networks 9 May 2025 · 0 repositories · arXiv:2505.05740
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Depth-Bounds for Neural Networks via the Braid Arrangement 13 Feb 2025 · 0 repositories · arXiv:2502.09324
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Deep Maxout Network-based Feature Fusion and Political Tangent Search Optimizer enabled Transfer Learning for Thalassemia Detection 3 Aug 2023 · 0 repositories · arXiv:2308.02029
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Query Structure Modeling for Inductive Logical Reasoning Over Knowledge Graphs 23 May 2023 · 1 repository · arXiv:2305.13585
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Error bounds for maxout neural network approximations of model predictive control 18 Apr 2023 · 0 repositories · arXiv:2304.08779
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Expected Gradients of Maxout Networks and Consequences to Parameter Initialization 17 Jan 2023 · 1 repository · arXiv:2301.06956
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Deep Maxout Network Gaussian Process 8 Aug 2022 · 0 repositories · arXiv:2208.04468
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On the Number of Regions of Piecewise Linear Neural Networks 17 Jun 2022 · 0 repositories · arXiv:2206.08615
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Learning with Stochastic Orders 27 May 2022 · 1 repository · arXiv:2205.13684
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Smooth Maximum Unit: Smooth Activation Function for Deep Networks Using Smoothing Maximum Technique 1 Jan 2022 · 0 repositories
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Learning Discriminative Shrinkage Deep Networks for Image Deconvolution 27 Nov 2021 · 1 repository · arXiv:2111.13876
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Time-Frequency Localization Using Deep Convolutional Maxout Neural Network in Persian Speech Recognition 9 Aug 2021 · 0 repositories · arXiv:2108.03818
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On the Expected Complexity of Maxout Networks 1 Jul 2021 · 1 repository · arXiv:2107.00379Syntology ran 3 of 4 samples · 1 unverified
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Revisiting 2D Convolutional Neural Networks for Graph-based Applications 23 May 2021 · 0 repositories · arXiv:2105.11016
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Maximum and Leaky Maximum Propagation 21 May 2021 · 0 repositories · arXiv:2105.10277
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Performance Evaluation of Deep Convolutional Maxout Neural Network in Speech Recognition 4 May 2021 · 0 repositories · arXiv:2105.01399
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Sharp bounds for the number of regions of maxout networks and vertices of Minkowski sums 16 Apr 2021 · 0 repositories · arXiv:2104.08135
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A new semi-supervised self-training method for lung cancer prediction 17 Dec 2020 · 0 repositories · arXiv:2012.09472
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Activate or Not: Learning Customized Activation 10 Sep 2020 · 5 repositories · arXiv:2009.04759
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Deep Neural-Kernel Machines 13 Jul 2020 · 0 repositories · arXiv:2007.06655
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CSPNet: A New Backbone that can Enhance Learning Capability of CNN 27 Nov 2019 · 123 repositories · arXiv:1911.11929
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Best Practices for Convolutional Neural Networks Applied to Object Recognition in Images 29 Oct 2019 · 0 repositories · arXiv:1910.13029
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Graph-Preserving Grid Layout: A Simple Graph Drawing Method for Graph Classification using CNNs 26 Sep 2019 · 0 repositories · arXiv:1909.12383
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Towards Learning Affine-Invariant Representations via Data-Efficient CNNs 31 Aug 2019 · 0 repositories · arXiv:1909.00114
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Conditional Computation for Continual Learning 16 Jun 2019 · 0 repositories · arXiv:1906.06635
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Max-plus Operators Applied to Filter Selection and Model Pruning in Neural Networks 19 Mar 2019 · 1 repository · arXiv:1903.08072
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Paragraph-level Neural Question Generation with Maxout Pointer and Gated Self-attention Networks 1 Oct 2018 · 1 repository
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Competition vs. Concatenation in Skip Connections of Fully Convolutional Networks 20 Jul 2018 · 0 repositories · arXiv:1807.07803
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A Tropical Approach to Neural Networks with Piecewise Linear Activations 22 May 2018 · 0 repositories · arXiv:1805.08749
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Single Image Super-Resolution Using Lightweight CNN with Maxout Units 7 Nov 2017 · 0 repositories · arXiv:1711.02321
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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