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20172023
most citedVariational Information Bottleneck on Vector Quantized Autoencoders

4 citations · 10 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023★ 1 cited

Inter-View Depth Consistency Testing in Depth Difference Subspace

Pravin Kumar Rana, Markus Flierl

Multiview depth imagery will play a critical role in free-viewpoint television. This technology requires high quality virtual view synthesis to enable viewers to move freely in a d…

cs.LG2020★ 3 cited

Conditional Mutual information-based Contrastive Loss for Financial Time Series Forecasting

Hanwei Wu, Ather Gattami, Markus Flierl

We present a representation learning framework for financial time series forecasting. One challenge of using deep learning models for finance forecasting is the shortage of availab…

eess.SP2020

Computing Similarity Queries for Correlated Gaussian Sources

Hanwei Wu, Qiwen Wang, Markus Flierl

Among many current data processing systems, the objectives are often not the reproduction of data, but to compute some answers based on the data resulting from queries. The similar…

cs.LG2019

Quantization-Based Regularization for Autoencoders

Hanwei Wu, Markus Flierl

Autoencoders and their variations provide unsupervised models for learning low-dimensional representations for downstream tasks. Without proper regularization, autoencoder models a…

cs.LG2018★ 4 cited

Variational Information Bottleneck on Vector Quantized Autoencoders

Hanwei Wu, Markus Flierl

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

eess.IV2018★ 2 cited

Learning Product Codebooks using Vector Quantized Autoencoders for Image Retrieval

Hanwei Wu, Markus Flierl

Vector-Quantized Variational Autoencoders (VQ-VAE)[1] provide an unsupervised model for learning discrete representations by combining vector quantization and autoencoders. In this…

cs.MM2017

Performance Analysis of Reliable Video Streaming with Strict Playout Deadline in Multi-Hop Wireless Networks

Hussein Al-Zubaidy, Viktoria Fodor, György Dán +1

Motivated by emerging vision-based intelligent services, we consider the problem of rate adaptation for high quality and low delay visual information delivery over wireless network…