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05/26/2023
High-Fidelity Image Compression with Score-based Generative Models
Despite the tremendous success of diffusion generative models in text-to...
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04/20/2023
Adaptive Greedy Rejection Sampling
We consider channel simulation protocols between two communicating parti...
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06/17/2022
Lossy Compression with Gaussian Diffusion
We describe a novel lossy compression approach called DiffC which is bas...
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02/14/2022
An Introduction to Neural Data Compression
Neural compression is the application of neural networks and other machi...
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10/29/2021
Optimal Compression of Locally Differentially Private Mechanisms
Compressing the output of ϵ-locally differentially private (LDP) randomi...
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10/25/2021
Algorithms for the Communication of Samples
We consider the problem of reverse channel coding, that is, how to simul...
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04/28/2021
A coding theorem for the rate-distortion-perception function
The rate-distortion-perception function (RDPF; Blau and Michaeli, 2019) ...
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02/18/2021
On the advantages of stochastic encoders
Stochastic encoders have been used in rate-distortion theory and neural ...
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06/17/2020
Universally Quantized Neural Compression
A popular approach to learning encoders for lossy compression is to use ...
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09/03/2019
Discriminative Topic Modeling with Logistic LDA
Despite many years of research into latent Dirichlet allocation (LDA), a...
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07/15/2019
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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04/02/2019
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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07/05/2018
Adaptive Paired-Comparison Method for Subjective Video Quality Assessment on Mobile Devices
To effectively evaluate subjective visual quality in weakly-controlled e...
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01/17/2018
Faster gaze prediction with dense networks and Fisher pruning
Predicting human fixations from images has recently seen large improveme...
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07/10/2017
Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize
The most prominent problem associated with the deconvolution layer is th...
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03/01/2017
Lossy Image Compression with Compressive Autoencoders
We propose a new approach to the problem of optimizing autoencoders for ...
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11/29/2016
Fast Face-swap Using Convolutional Neural Networks
We consider the problem of face swapping in images, where an input ident...
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10/14/2016
Amortised MAP Inference for Image Super-resolution
Image super-resolution (SR) is an underdetermined inverse problem, where...
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09/22/2016
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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09/15/2016
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Despite the breakthroughs in accuracy and speed of single image super-re...
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11/05/2015
A note on the evaluation of generative models
Probabilistic generative models can be used for compression, denoising, ...
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06/10/2015
Generative Image Modeling Using Spatial LSTMs
Modeling the distribution of natural images is challenging, partly becau...
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05/28/2015
A Generative Model of Natural Texture Surrogates
Natural images can be viewed as patchworks of different textures, where ...
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05/28/2015
A trust-region method for stochastic variational inference with applications to streaming data
Stochastic variational inference allows for fast posterior inference in ...
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02/28/2015
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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11/04/2014
Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet
Recent results suggest that state-of-the-art saliency models perform far...
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10/17/2014
Inference and Mixture Modeling with the Elliptical Gamma Distribution
We study modeling and inference with the Elliptical Gamma Distribution (...
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09/20/2011
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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11/28/2010
