A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference
[article]
2017
arXiv
pre-print
Preserved Fulltext
Other Versions
Semi-supervised learning methods using Generative Adversarial Networks (GANs) have shown promising empirical success recently. ...
Motivated by the ability of the GANs generator to capture the data manifold well, we propose to estimate the tangent space to the data manifold using GANs and employ it to inject invariances into the classifier ...
In this work we make following contributions: • We propose to use the tangents from the generator's mapping to automatically infer the desired invariances and further improve on semi-supervised learning ...
arXiv:1705.08850v2
fatcat:bhvyhsbujfenvprmi6ttvpy4vu
Semi-Supervised Learning with GANs: Revisiting Manifold Regularization
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
When incorporated into the feature-matching GAN of Improved GAN, we achieve state-of-the-art results for GAN-based semi-supervised learning on the CIFAR-10 dataset, with a method that is significantly ...
We leverage this property to perform manifold regularization by approximating the Laplacian norm using a Monte Carlo approximation that is easily computed with the GAN. ...
When applied to the feature-matching GAN, we achieve state-of-the-art performance amongst GAN-based methods for semi-supervised learning. ...
arXiv:1805.08957v1
fatcat:47yci44ahnawxiszwwbhpz2wtu
Consistency Regularization with Generative Adversarial Networks for Semi-Supervised Learning
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Generative Adversarial Networks (GANs) based semi-supervised learning (SSL) approaches are shown to improve classification performance by utilizing a large number of unlabeled samples in conjunction with ...
Our experiments show that this new composite consistency regularization based semi-GAN significantly improves its performance and achieves new state-of-the-art performance among GAN-based SSL approaches ...
discriminator of semi-GAN, encouraging it to make consistent predictions for data under perturbations, thus leading to improved semi-supervised classification. ...
arXiv:2007.03844v2
fatcat:2iu34ftqtbgzvlgflzjx6w4lqy
Local Clustering with Mean Teacher for Semi-supervised Learning
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
semi-supervised learning. ...
We demonstrate on semi-supervised benchmark datasets SVHN and CIFAR-10 that adding our LC loss to MT yields significant improvements compared to MT and performance comparable to the state of the art in ...
on a data manifold. ...
arXiv:2004.09665v2
fatcat:uk766o5ynzhmdhudtk3gziyiie
Semi-Supervised Learning with the Deep Rendering Mixture Model
[article]
2016
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Taken together, our work provides a unified framework for supervised, unsupervised, and semi-supervised learning. ...
Semi-supervised learning algorithms reduce the high cost of acquiring labeled training data by using both labeled and unlabeled data during learning. ...
For semi-supervised learning tasks on CIFAR10, the Improved GAN has the best classification error (18.63% and 17.72% test errors when N L ∈ {4K, 8K}). ...
arXiv:1612.01942v1
fatcat:q2onfll7qvcynm3n5azwrlb7em
Semi-supervised Learning using Adversarial Training with Good and Bad Samples
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In this work, we investigate semi-supervised learning (SSL) for image classification using adversarial training. ...
Triple-GAN, which aims to jointly optimize model components by incorporating three players, generates suitable image-label pairs to compensate for the lack of labeled data in SSL with improved benchmark ...
Conclusions We have presented unified-GAN (UGAN), a new GAN framework for semi-supervised learning. ...
arXiv:1910.08540v1
fatcat:522qihzzunesldxoqvsjfs6mwi
Attribute Guided Unpaired Image-to-Image Translation with Semi-supervised Learning
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Especially, AGUIT benefits from two-fold: (1) It adopts a novel semi-supervised learning process by translating attributes of labeled data to unlabeled data, and then reconstructing the unlabeled data ...
AGUIT considers multi-modal and multi-domain tasks of UIT jointly with a novel semi-supervised setting, which also merits in representation disentanglement and fine control of outputs. ...
Several recent works leveraged GANs for semi-supervised learning of classification Step I. Representation Decomposition Step II. Reconstruction and Translation Step III. ...
arXiv:1904.12428v1
fatcat:vifa3uqt5ralrb7pdnd2ojrzii
Partition-Guided GANs
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Despite the success of Generative Adversarial Networks (GANs), their training suffers from several well-known problems, including mode collapse and difficulties learning a disconnected set of manifolds ...
In this paper, we break down the challenging task of learning complex high dimensional distributions, supporting diverse data samples, to simpler sub-tasks. ...
[49] , motivated by the better performance of supervised-GANs, propose using a small set of labels and a semi-supervised method to infer the labels for the entire data. ...
arXiv:2104.00816v2
fatcat:n2q5zfbx7jfybfawg26xk6orgm
RoCGAN: Robust Conditional GAN
2020
International Journal of Computer Vision
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
The focus so far has largely been on performance improvement, with little effort in making cGANs more robust to noise. ...
We prove that RoCGAN share similar theoretical properties as GAN and establish with both synthetic and real data the merits of our model. ...
We learn this structure with an unsupervised module which is included along with our supervised pathway. ...
doi:10.1007/s11263-020-01348-5
fatcat:dep7zvp4ene23dlg42qw42vdza
Improving GAN Training via Binarized Representation Entropy (BRE) Regularization
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The approach also leads to higher classification accuracies in semi-supervised learning. ...
We propose a novel regularizer to improve the training of Generative Adversarial Networks (GANs). ...
Table. 2 shows results on CIFAR10 with feature matching semi-supervised learning GAN. ...
arXiv:1805.03644v1
fatcat:pq3levwpcbhcjaornzetrnqhu4
Yes, we GAN: Applying Adversarial Techniques for Autonomous Driving
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
This paper focuses on the application of GAN in autonomous driving including topics such as advanced data augmentation, loss function learning, semi-supervised learning, etc. ...
Research on GAN is rapidly growing and there are many variants of the original GAN focusing on various aspects of deep learning. ...
We would also like to thank the company Borealis AI for the GAN T-shirts which inspired the title of this paper 4 . ...
arXiv:1902.03442v1
fatcat:ev4dkg6wq5cjvbuy6htwlojzda
Semi-supervised and weakly-supervised learning with spatio-temporal priors in medical image segmentation
2021
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
We make this possible by constraining the data representation learned by our method to be semantic or by regularising the model predictions to satisfy data-driven spatio-temporal priors. ...
With the advent of faster and higher-quality imaging technologies, the amount of data that is possible to collect for each patient is paving the way toward personalised medicine. ...
model and improve test-time performance in semi-supervised learning. ...
doi:10.13118/imtlucca/e-theses/344/
fatcat:qru63k6hibed3pwtxemhd523ua
Pairwise Augmented GANs with Adversarial Reconstruction Loss
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
We propose a novel autoencoding model called Pairwise Augmented GANs. We train a generator and an encoder jointly and in an adversarial manner. ...
Here we train a discriminator to distinguish two types of pairs: an object with its augmentation and the one with its reconstruction. ...
For example, it is used in semi-supervised learning , in a manipulation of object properties using low dimensional manifold (Creswell et al., 2017) and in an optimization utilizing the known structure ...
arXiv:1810.04920v1
fatcat:cgmhncnl4vbuhbb4yzulcgw5ty
DNA-GAN: Learning Disentangled Representations from Multi-Attribute Images
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In this paper, we propose a supervised learning model called DNA-GAN which tries to disentangle different factors or attributes of images. ...
images with the existence of the corresponding attribute being changed. ...
In the semi-supervised setting, Siddharth et al. (2016) tried to learn a disentangled representations by using an auxiliary variable. ...
arXiv:1711.05415v2
fatcat:upgqokc7afb5tppmqz2hkuu6hm
Survey on Implementations of Generative Adversarial Networks for Semi-Supervised Learning
2022
Applied Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Given recent advances in deep learning, semi-supervised techniques have seen a rise in interest. ...
Generative adversarial networks (GANs) represent one recent approach to semi-supervised learning (SSL). This paper presents a survey method using GANs for SSL. ...
GANs for semi-supervised learning. ...
doi:10.3390/app12031718
fatcat:x4skf2zvvvfornkmhelaijiwwu
« Previous
Showing results 1 — 15 out of 548 results