8 citations · 8 across the 3 of their papers we have counts for
3 papers · 1 filter
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…
Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning
Daniel Becking, Heiner Kirchhoffer, Gerhard Tech +4
Federated learning (FL) scenarios inherently generate a large communication overhead by frequently transmitting neural network updates between clients and server. To minimize the c…
DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression
Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage +9
We present DeepCABAC, a novel context-adaptive binary arithmetic coder for compressing deep neural networks. It quantizes each weight parameter by minimizing a weighted rate-distor…