Research graph
References from Deep Feature Learning with Concatenated Rectified Pooling Units. Local targets link to admitted publications; unresolved targets remain external evidence.
10.1038/d41586-023-00816-5
10.1038/d41586-023-00816-5 · External reference
AI creating new photo ops
2023 · External reference
Unresolved reference
2016 · External reference
10.1038/d41586-023-02361-7
10.1038/d41586-023-02361-7 · External reference
10.1007/978-981-10-5209-5_6
10.1007/978-981-10-5209-5_6 · External reference
Deep learning for NLP (without magic)
2012 · External reference
10.5244/c.29.41
10.5244/c.29.41 · External reference
10.1109/iske47853.2019.9170280
10.1109/iske47853.2019.9170280 · External reference
Deep learning techniques for music generation—A survey
2017 · External reference
10.1145/3368089.3417058
10.1145/3368089.3417058 · External reference
10.18653/v1/d19-5611
10.18653/v1/d19-5611 · External reference
10.55525/tjst.1272369
10.55525/tjst.1272369 · External reference
10.1109/wacv48630.2021.00391
10.1109/wacv48630.2021.00391 · External reference
10.1109/access.2024.3365742
10.1109/access.2024.3365742 · External reference
10.1109/iccvw.2019.00099
10.1109/iccvw.2019.00099 · External reference
10.1609/aaai.v31i1.10913
10.1609/aaai.v31i1.10913 · External reference
The low-rank simplicity bias in deep networks
2021 · External reference
10.1007/bf02551274
10.1007/bf02551274 · External reference
10.1016/0893-6080(89)90020-8
10.1016/0893-6080(89)90020-8 · External reference
10.26599/bdma.2019.9020024
10.26599/bdma.2019.9020024 · External reference
Understanding and improving convolutional neural networks via concatenated rectified linear units
2016 · External reference
Revise saturated activation functions
2016 · External reference
10.1007/978-3-030-14880-5_1
10.1007/978-3-030-14880-5_1 · External reference
10.1109/icip.2016.7533046
10.1109/icip.2016.7533046 · External reference
10.4208/cicp.oa-2020-0149
10.4208/cicp.oa-2020-0149 · External reference
Unresolved reference
2020 · External reference
10.1109/tccn.2019.2948919
10.1109/tccn.2019.2948919 · External reference
The power of deeper networks for expressing natural functions
2018 · External reference
10.1016/0004-3702(92)90065-6
10.1016/0004-3702(92)90065-6 · External reference
Understanding the difficulty of training deep feedforward neural networks
2010 · External reference
BinaryConnect: Training deep neural networks with binary weights during propagations
2015 · External reference
10.1016/j.neunet.2017.12.012
10.1016/j.neunet.2017.12.012 · External reference
Searching for activation functions
2018 · External reference
10.1038/nature14539
10.1038/nature14539 · External reference
Performance analysis of various activation functions in generalized MLP architectures of neural networks
2011 · External reference
10.1017/9781108684163.013
10.1017/9781108684163.013 · External reference
Natural language processing (almost) from scratch
2011 · External reference
10.3115/1620853.1620921
10.3115/1620853.1620921 · External reference
10.5555/3104322.3104425
10.5555/3104322.3104425 · External reference
10.1109/icassp.2013.6638312
10.1109/icassp.2013.6638312 · External reference
Understanding deep neural networks with rectified linear units
2016 · External reference
Reliably learning the ReLU in polynomial time
2017 · External reference
10.1145/3299815.3314450
10.1145/3299815.3314450 · External reference
Rectifier nonlinearities improve neural network acoustic models
2013 · External reference
10.1109/iccv.2015.123
10.1109/iccv.2015.123 · External reference
Empirical evaluation of rectified activations in convolutional network
2015 · External reference
10.1109/icpr.2018.8546022
10.1109/icpr.2018.8546022 · External reference
Incorporating second-order functional knowledge for better option pricing
2000 · External reference
Fast and accurate deep network learning by exponential linear units (ELUs)
2016 · External reference
10.1109/icmla.2017.00038
10.1109/icmla.2017.00038 · External reference
10.1109/icpr.2018.8545104
10.1109/icpr.2018.8545104 · External reference
Maxout networks
2013 · External reference
10.1016/j.neucom.2017.07.061
10.1016/j.neucom.2017.07.061 · External reference
Multi-bias non-linear activation in deep neural networks
2016 · External reference
10.1007/s10955-017-1836-5
10.1007/s10955-017-1836-5 · External reference
10.1016/j.neunet.2018.08.019
10.1016/j.neunet.2018.08.019 · External reference
10.1145/3284174
10.1145/3284174 · External reference
10.1109/bdcloud-socialcom-sustaincom.2016.27
10.1109/bdcloud-socialcom-sustaincom.2016.27 · External reference
10.5555/3015812.3015979
10.5555/3015812.3015979 · External reference
10.1109/iccv.2015.336
10.1109/iccv.2015.336 · External reference
10.5555/3295222.3295371
10.5555/3295222.3295371 · External reference
10.1016/j.acha.2016.04.003
10.1016/j.acha.2016.04.003 · External reference
10.1073/pnas.1907369117
10.1073/pnas.1907369117 · External reference
10.1142/s0219530516400042
10.1142/s0219530516400042 · External reference
Learning functions: When is deep better than shallow
2016 · External reference
10.1145/3065386
10.1145/3065386 · External reference
Convolutional deep belief networks on CIFAR-10
2010 · External reference
10.1109/jrfid.2021.3051901
10.1109/jrfid.2021.3051901 · External reference
Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms
2017 · External reference
Unresolved reference
2009 · External reference
10.1109/tmm.2022.3145663
10.1109/tmm.2022.3145663 · External reference
