1.1k citations · 2.6k across the 12 of their papers we have counts for
13 papers
Optimizing Learned Image Compression on Scalar and Entropy-Constraint Quantization
Florian Borzechowski, Michael Schäfer, Heiko Schwarz +3
The continuous improvements on image compression with variational autoencoders have lead to learned codecs competitive with conventional approaches in terms of rate-distortion effi…
Efficient and Flexible Neural Network Training through Layer-wise Feedback Propagation
Leander Weber, Jim Berend, Moritz Weckbecker +4
Gradient-based optimization has been a cornerstone of machine learning that enabled the vast advances of Artificial Intelligence (AI) development over the past decades. However, th…
Curiously Effective Features for Image Quality Prediction
Sören Becker, Thomas Wiegand, Sebastian Bosse
The performance of visual quality prediction models is commonly assumed to be closely tied to their ability to capture perceptually relevant image aspects. Models are thus either b…
FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4bit-Compact Multilayer Perceptrons
Simon Wiedemann, Suhas Shivapakash, Pablo Wiedemann +4
With the growing demand for deploying deep learning models to the "edge", it is paramount to develop techniques that allow to execute state-of-the-art models within very tight and…
Risk Estimation of SARS-CoV-2 Transmission from Bluetooth Low Energy Measurements
Felix Sattler, Jackie Ma, Patrick Wagner +6
Digital contact tracing approaches based on Bluetooth low energy (BLE) have the potential to efficiently contain and delay outbreaks of infectious diseases such as the ongoing SARS…
Trends and Advancements in Deep Neural Network Communication
Felix Sattler, Thomas Wiegand, Wojciech Samek
Due to their great performance and scalability properties neural networks have become ubiquitous building blocks of many applications. With the rise of mobile and IoT, these models…