
A coding theorem for the ratedistortionperception function
The ratedistortionperception function (RDPF; Blau and Michaeli, 2019) ...
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On the advantages of stochastic encoders
Stochastic encoders have been used in ratedistortion theory and neural ...
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Universally Quantized Neural Compression
A popular approach to learning encoders for lossy compression is to use ...
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Discriminative Topic Modeling with Logistic LDA
Despite many years of research into latent Dirichlet allocation (LDA), a...
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Addressing Delayed Feedback for Continuous Training with Neural Networks in CTR prediction
One of the challenges in display advertising is that the distribution of...
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HoloGAN: Unsupervised learning of 3D representations from natural images
We propose a novel generative adversarial network (GAN) for the task of ...
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Adaptive PairedComparison Method for Subjective Video Quality Assessment on Mobile Devices
To effectively evaluate subjective visual quality in weaklycontrolled e...
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Faster gaze prediction with dense networks and Fisher pruning
Predicting human fixations from images has recently seen large improveme...
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Checkerboard artifact free subpixel convolution: A note on subpixel convolution, resize convolution and convolution resize
The most prominent problem associated with the deconvolution layer is th...
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Lossy Image Compression with Compressive Autoencoders
We propose a new approach to the problem of optimizing autoencoders for ...
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Fast Faceswap Using Convolutional Neural Networks
We consider the problem of face swapping in images, where an input ident...
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Amortised MAP Inference for Image Superresolution
Image superresolution (SR) is an underdetermined inverse problem, where...
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Is the deconvolution layer the same as a convolutional layer?
In this note, we want to focus on aspects related to two questions most ...
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PhotoRealistic Single Image SuperResolution Using a Generative Adversarial Network
Despite the breakthroughs in accuracy and speed of single image superre...
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A note on the evaluation of generative models
Probabilistic generative models can be used for compression, denoising, ...
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Generative Image Modeling Using Spatial LSTMs
Modeling the distribution of natural images is challenging, partly becau...
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A Generative Model of Natural Texture Surrogates
Natural images can be viewed as patchworks of different textures, where ...
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A trustregion method for stochastic variational inference with applications to streaming data
Stochastic variational inference allows for fast posterior inference in ...
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Supervised learning sets benchmark for robust spike detection from calcium imaging signals
A fundamental challenge in calcium imaging has been to infer the timing ...
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Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet
Recent results suggest that stateoftheart saliency models perform far...
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Inference and Mixture Modeling with the Elliptical Gamma Distribution
We study modeling and inference with the Elliptical Gamma Distribution (...
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Mixtures of conditional Gaussian scale mixtures applied to multiscale image representations
We present a probabilistic model for natural images which is based on Ga...
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In All Likelihood, Deep Belief Is Not Enough
Statistical models of natural stimuli provide an important tool for rese...
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