… channel is an important endeavor involving deep mathematical research and wideranging …
of codes obtained via deep learning, which significantly beats state-of-the-art codes designed …

… is a model that captures the essence of channels with feedback; this … codes for this channel
via deep learning approaches is the central focus of this paper. Whereas the output feedback …

… an analytical analysis of deep-learned codes for the point-to-point channels without feedback
[18]. … of deep-learned codes for channels with and without feedback besides this work. …

… deep-neural-network (DNN) based error correction encoder architecture for channels with
feedback, called Deep Extended Feedback (… the transmitter through a feedback channel. DEF …

… In this paper, we develop a new family of non-linear feedback codes that greatly enhance
robustness to channel noise. Our autoencoderbased architecture is designed to learn codes …

… of deep learning methods for JSCC, we investigate how noiseless or noisy channel output
feedback can … existing channel codes, such as linear [23], turbo [24], or polar [25] codes, which …

… of DRF codes in multicast channels with feedback, where linear feedback codes are known
… Smelyanskiy, and PTP Tang, “On large-batch training for deep learning: Generalization gap …

… In 2014, we presented a nonlinear feedback coding scheme based on a combination of the
… attainable by any forward error correction code (without feedback) using block lengths of N = …

… user-feedback-related source code and having been inspired by the recent progress of
applying deep learning in IR, we propose Feedback2Code, a deep learning approach that …

… For the source code, we consider well established image compression algorithms: JPEG,
JPEG2000 and BPG. For fair comparison, we remove the header information from the …