Search Results - "Vector quantized autoencoder"

Avoiding Domain Drift and Constant Predictions with Diffusion Enhanced Vector-Quantized Autoencoders for Temperature Predictions by Lampl, Nina, de Freitas, Joao Machado, Fuchs, Alexander, Brezina, Benedikt, Klitzsch, Michael, Pernkopf, Franz

“… Using a vector-quantized autoencoder can mitigate the problem as it can map predictions back to the source domain, but it leads to almost constant predictions…”
Get full text

A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow by Momenifar, Mohammadreza, Diao, Enmao, Tarokh, Vahid, Bragg, Andrew D.

“…Analyzing large-scale data from simulations of turbulent flows is memory intensive, requiring significant resources. This major challenge highlights the need…”
Get full text

A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow by Momenifar, Mohammadreza, Diao, Enmao, Tarokh, Vahid, Bragg, Andrew D

“…Analyzing large-scale data from simulations of turbulent flows is memory intensive, requiring significant resources. This major challenge highlights the need…”
Get full text

Variable Rate Allocation for Vector-Quantized Autoencoders by Baldassarre, Federico, El-Nouby, Alaaeldin, Jegou, Herve

“…Vector-quantized autoencoders have recently gained interest in image compression, generation and self-supervised learning…”
Get full text

Enhancing into the Codec: Noise Robust Speech Coding with Vector-Quantized Autoencoders by Casebeer, Jonah, Vale, Vinjai, Isik, Umut, Valin, Jean-Marc, Giri, Ritwik, Krishnaswamy, Arvindh

“…Audio codecs based on discretized neural autoencoders have recently been developed and shown to provide significantly higher compression levels for comparable…”
Get full text

Group Residual Vector Quantized Autoencoders for SAR Raw Data Compression by Pilikos, Georgios, Azcueta, Mario, Floury, Nicolas

“…Synthetic Aperture Radar (SAR) systems are being improved continuously with increased swath sizes, better spatial resolution, multi-frequency and multi-channel…”
Get full text

Learning Product Codebooks Using Vector-Quantized Autoencoders for Image Retrieval by Wu, Hanwei, Flierl, Markus

“…Vector-Quantized Variational Autoencoders (VQ-VAE)[1] provide an unsupervised model for learning discrete representations by combining vector quantization and…”
Get full text

Harnessing the Power of Pre-Trained Models for Efficient Semantic Communication of Text and Images by Kutay, Emrecan, Yener, Aylin

“…This paper investigates point-to-point multimodal digital semantic communications in a task-oriented setup, where messages are classified at the receiver. We…”
Get full text

Theory and Experiments on Vector Quantized Autoencoders by Aurko Roy, Vaswani, Ashish, Neelakantan, Arvind, Parmar, Niki

“… and their performance has mostly failed to match their continuous counterparts. Recent work on vector quantized autoencoders (VQ-VAE…”
Get full text

Variational Information Bottleneck on Vector Quantized Autoencoders by Wu, Hanwei, Flierl, Markus

“…In this paper, we provide an information-theoretic interpretation of the Vector Quantized-Variational Autoencoder (VQ-VAE). We show that the loss function of…”
Get full text

Enhancing into the codec: Noise Robust Speech Coding with Vector-Quantized Autoencoders by Casebeer, Jonah, Vale, Vinjai, Isik, Umut, Valin, Jean-Marc, Giri, Ritwik, Krishnaswamy, Arvindh

“…Audio codecs based on discretized neural autoencoders have recently been developed and shown to provide significantly higher compression levels for comparable…”
Get full text

Learning Product Codebooks using Vector Quantized Autoencoders for Image Retrieval by Wu, Hanwei, Flierl, Markus

“…Vector-Quantized Variational Autoencoders (VQ-VAE)[1] provide an unsupervised model for learning discrete representations by combining vector quantization and…”
Get full text

Learning Sampling in Financial Statement Audits using Vector Quantised Autoencoder Neural Networks by Schreyer, Marco, Sattarov, Timur, Gierbl, Anita, Reimer, Bernd, Borth, Damian

“…The audit of financial statements is designed to collect reasonable assurance that an issued statement is free from material misstatement 'true and fair…”
Get full text

Vector-Quantized Latent Flows for Medical Image Synthesis and Out-Of-Distribution Detection by Khader, Firas, Muller-Franzes, Gustav, Arasteh, Soroosh Tayebi, Han, Tianyu, Kather, Jakob Nikolas, Stegmaier, Johannes, Nebelung, Sven, Truhn, Daniel

“…We present an innovative method that allows for simultaneous out-of-distribution detection and image generation by encoding images in the latent space of a vector-quantized autoencoder and using normalizing flow models…”
Get full text

Classification-Oriented Semantic Wireless Communications by Kutay, Emrecan, Yener, Aylin

“… In the learning-based approach, we use a semantic vector quantized autoencoder model that learns a codebook from scratch…”
Get full text

Speech Watermarking with Discrete Intermediate Representations by Ji, Shengpeng, Jiang, Ziyue, Zuo, Jialong, Fang, Minghui, Chen, Yifu, Jin, Tao, Zhou, Zhao

“… Specifically, we map speech into discrete latent space with a vector-quantized autoencoder and inject watermarks by changing the modular arithmetic…”
Get full text

GPD-1: Generative Pre-training for Driving by Xie, Zixun, Zuo, Sicheng, Zheng, Wenzhao, Zhang, Yunpeng, Du, Dalong, Zhou, Jie, Lu, Jiwen, Zhang, Shanghang

“…Modeling the evolutions of driving scenarios is important for the evaluation and decision-making of autonomous driving systems. Most existing methods focus on…”
Get full text

VQalAttent: a Transparent Speech Generation Pipeline based on Transformer-learned VQ-VAE Latent Space by Rodriguez, Armani, Kokalj-Filipovic, Silvija

“…: first, a scalable vector quantized autoencoder (VQ-VAE) that compresses audio spectrograms into discrete latent representations, and second, a decoder-only transformer that learns the probability model of these latents…”
Get full text

Classification-Oriented Semantic Wireless Communications by Kutay, Emrecan, Yener, Aylin

“… In the learning-based approach, we use a semantic vector quantized autoencoder model that learns a codebook from scratch…”
Get full text

QPoser: Quantized Explicit Pose Prior Modeling for Controllable Pose Generation by Li, Yumeng, Ding, Yaoxiang, Ren, Zhong, Zhou, Kun

“… In QPoser, a multi-head vector quantized autoencoder (MS-VQVAE) is proposed for obtaining expressive and distributed pose representations…”
Get full text