[PDF] Top 20 Biconditional Generative Adversarial Networks for Multiview Learning with Missing Views
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Biconditional Generative Adversarial Networks for Multiview Learning with Missing Views
... generated views within our approach com- pared to when they are generated using MT (Section ...work Multiview learning has been an active domain of research these past few ...techniques for ... Voir le document complet
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On the consistency of supervised learning with missing values
... ). Missing entries can then be imputed with their conditional expectation knowing the observed data and the estimated ...deep learning ap- proaches such as denoising autoencoders (DAEs, Vincent et ... Voir le document complet
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LIGHT FIELD IMAGE CODING USING DUAL DISCRIMINATOR GENERATIVE ADVERSARIAL NETWORK AND VVC TEMPORAL SCALABILITY
... straight for- ward coding approach organizes the LF views in a pseudo video sequence, which is then encoded with a classical 2D hybrid video encoder [4, 5, ...of views using a video encoder, ... Voir le document complet
7
Multi-view Generative Adversarial Networks
... Representation Learning: Many application fields naturally deal with multi-view data with true ...advantages. For example, in the multimedia domain, dealing with a bunch of views ... Voir le document complet
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Toward quantitative three-dimensional microvascular networks segmentation with multiview light-sheet fluorescence microscopy
... elements for the usefulness and future extensions of the presented ...associated with the image processing workflow, ...of views for each ves- sel, even considering local deformations sized to ... Voir le document complet
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How to deal with missing data in supervised deep learning?
... of missing data in supervised learn- ing has been largely overlooked, especially in the deep learning ...be missing at ...the missing values with learn- able ...jointly with the ... Voir le document complet
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GenPR: Generative PageRank Framework for Semi-supervised Learning on Citation Graphs
... Semi-Supervised Learning (SSL) on citation graph data sets is a rapidly growing area of ...matrix with binary weights on edges (citations), that causes a loss of the nodes (pa- pers) similarity ...a ... Voir le document complet
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On the Existence of Optimal Transport Gradient for Learning Generative Models
... end for We now consider the application of Algorithm 1 to the learning of a generative model on the MNIST dataset with the cost c(x, y) = kx − yk 2 ...The generative model we considered ... Voir le document complet
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From attribute-labels to faces: face generation using a conditional generative adversarial network
... the learning of a text fea- ture representation that captures the important visual details, as well as (ii) given the features, the generation of compelling realistic ...convolutional generative ... Voir le document complet
7
Toward quantitative three-dimensional microvascular networks segmentation with multiview light-sheet fluorescence microscopy
... interest for the analy- sis of low- to high-level structural properties of vascular net- ...response with the num- ber n of views, i.e., four views > three views > two ... Voir le document complet
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A generative-discriminative learning model for noisy information fusion
... argument for the latter case since it stands to reason that multisensory integration in biological systems is not generally innate but learned ...desirable for intelligent agents to ...layer with a ... Voir le document complet
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Discriminative vs. Generative Classifiers for Cost Sensitive Learning
... and generative classifiers. It focuses on cost sensitive learning when the misclassification costs, and class frequencies, may change, or are simply unknown ahead of ...machine learning communities ... Voir le document complet
14
Online Learning in Adversarial Lipschitz Environments
... between regret and numerical complexity, which is illustrated by numerical ex- periments in Section 1.3 where PMC techniques are compared to sampling from uniform grids. Then in Section 2 we describe several ... Voir le document complet
17
How Do Scientific Views Change? Notes From an Extended Adversarial Collaboration
... meetings are important and that each side will need considerable time to express their views and enter into discussions. We therefore recommend two to four laboratories, perhaps more than coincidentally similar ... Voir le document complet
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On the Relationships between Generative Encodings, Regularity, and Learning Abilities when Evolving Plastic Artificial Neural Networks
... neural networks using neuro- modulated Hebbian plasticity [2,7,21,23] ...threshold. For each association of E, the fitness function first presents the stimuli to the neural network for a few ... Voir le document complet
13
Variational methods for tomographic reconstruction with few views
... and an inspection of Figure 3.2 (d) shows that the use of the inverse operator is not suitable. 3.1. A first variational model We first proposed in [ 4 ] a variational method based on a minimization prob- lem in the ... Voir le document complet
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Augmenting physics simulators with neural networks for model learning and control
... Our work mainly focuses on leveraging prior models (like analytical dynamics models, physics engine) to learn residual dynamics model between the prior model and r[r] ... Voir le document complet
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Structured prediction and generative modeling using neural networks
... neural networks to effectively model data with sequen- tial ...data for which both the order and the structure of the information is ncredibly ...present generative models, which attempt to ... Voir le document complet
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Simultaneous super-resolution and segmentation using a generative adversarial network: Application to neonatal brain MRI
... sults with significant improvement with respect to the two other ...obtained with SegSRGAN (applied on interpolated ...approach for fine analysis of clinical neonatal brain ... Voir le document complet
5
Variational methods for tomographic reconstruction with few views
... (see for instance [ 22 ]) As in any tomographic recon- struction process, this problem leads to an ill-posed inverse ...appear, for instance the X-rays beam is not well focused and the X-rays source is not ... Voir le document complet
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