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Related papers: Gradient Flow Decoding

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A recent line of work has focused on the use of low-density generator matrix (LDGM) codes for lossy source coding. In this paper, wedevelop a generic technique for deriving lower bounds on the rate-distortion functions of binary linear…

Information Theory · Computer Science 2008-08-18 A. G. Dimakis , M. J. Wainwright , K. Ramchandran

Gradient descent (GD) methods are commonly employed in machine learning problems to optimize the parameters of the model in an iterative fashion. For problems with massive datasets, computations are distributed to many parallel computing…

Information Theory · Computer Science 2019-03-06 Emre Ozfatura , Deniz Gunduz , Sennur Ulukus

Motion-based video frame interpolation (VFI) methods have made remarkable progress with the development of deep convolutional networks over the past years. While their performance is often jeopardized by the inaccuracy of flow map…

Computer Vision and Pattern Recognition · Computer Science 2022-11-23 Pengcheng Lei , Faming Fang , Guixu Zhang

We consider the decoding of LDPC codes over GF(q) with the low-complexity majority algorithm from [1]. A modification of this algorithm with multiple thresholds is suggested. A lower estimate on the decoding radius realized by the new…

Information Theory · Computer Science 2015-02-25 Alexey Frolov , Victor Zyablov

This paper addresses the prediction of error floors of low-density parity-check (LDPC) codes with variable nodes of constant degree in the additive white Gaussian noise (AWGN) channel. Specifically, we focus on the performance of the…

Information Theory · Computer Science 2013-06-11 Brian K. Butler , Paul H. Siegel

Stochastic Gradient Descent (SGD) has been the method of choice for learning large-scale non-convex models. While a general analysis of when SGD works has been elusive, there has been a lot of recent progress in understanding the…

Machine Learning · Computer Science 2022-10-14 Satyen Kale , Jason D. Lee , Chris De Sa , Ayush Sekhari , Karthik Sridharan

Enhancing the efficiency of high-quality image generation using Diffusion Models (DMs) is a significant challenge due to the iterative nature of the process. Flow Matching (FM) is emerging as a powerful generative modeling paradigm based on…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Pascal Zwick , Nils Friederich , Maximilian Beichter , Lennart Hilbert , Ralf Mikut , Oliver Bringmann

We introduce a decoding framework for correlated errors in quantum LDPC codes under circuit-level noise. The core of our approach is a graph augmentation and rewiring for interference (GARI) method, which modifies the correlated detector…

Quantum Physics · Physics 2026-03-26 Arshpreet Singh Maan , Francisco-Garcia Herrero , Alexandru Paler , Valentin Savin

Gradient Descent (GD) and its variants are the primary tool for enabling efficient training of recurrent dynamical systems such as Recurrent Neural Networks (RNNs), Neural ODEs and Gated Recurrent units (GRUs). The dynamics that are formed…

Machine Learning · Computer Science 2025-07-10 James Hazelden , Laura Driscoll , Eli Shlizerman , Eric Shea-Brown

This work introduces a novel, fully differentiable linear-time complexity transformer decoder and a transformer decoder to correct 5G New Radio (NR) LDPC. We propose a scalable approach to decode linear block codes with $O(n)$ complexity…

Machine Learning · Computer Science 2025-01-27 Mario Hernandez , Fernando Pinero

In this work, we introduce a new hardware architecture for decoding correlated errors in quantum LDPC codes. The decoder is based on message passing and exploits the structure of the detector error model obtained through the recently…

The autoencoder model typically uses an encoder to map data to a lower dimensional latent space and a decoder to reconstruct it. However, relying on an encoder for inversion can lead to suboptimal representations, particularly limiting in…

Machine Learning · Statistics 2025-01-07 Kyriakos Flouris , Anna Volokitin , Gustav Bredell , Ender Konukoglu

This paper considers the joint-decoding (JD) problem for finite-state channels (FSCs) and low-density parity-check (LDPC) codes. In the first part, the linear-programming (LP) decoder for binary linear codes is extended to JD of…

Information Theory · Computer Science 2015-05-27 Byung-Hak Kim , Henry D. Pfister

The development of multicore architectures supporting parallel data processing has led to a paradigm shift, which affects communication systems significantly. This article provides a scalable parallel approach of an iterative LDPC decoder,…

Information Theory · Computer Science 2020-01-31 Jan Broulim , Alexander Ayriyan , Vjaceslav Georgiev , Hovik Grigorian

Due to the speed limitation of the conventional bit-chosen strategy in the existing weighted bit flipping algorithms, a high-speed LDPC decoder cannot be realized. To solve this problem, we propose a fast weighted bit flipping (FWBF)…

Information Theory · Computer Science 2012-06-18 Kexiang Ma , Yongzhao Li , Caizhi Zhu , Hailin Zhang , Feng Qi

We investigate joint source channel coding (JSCC) for wireless image transmission over multipath fading channels. Inspired by recent works on deep learning based JSCC and model-based learning methods, we combine an autoencoder with…

Signal Processing · Electrical Eng. & Systems 2021-09-14 Mingyu Yang , Chenghong Bian , Hun-Seok Kim

In this paper, we focus on the two-user Gaussian interference channel (GIC), and study the Han-Kobayashi (HK) coding/decoding strategy with the objective of designing low-density parity-check (LDPC) codes. A code optimization algorithm is…

Information Theory · Computer Science 2014-05-27 Shahrouz Sharifi , A. Korhan Tanc , Tolga M. Duman

In this paper, we study a compute-and-forward (CAF) relaying scheme with low-density parity-check (LDPC) codes, a special case of physical layer network coding, under the quadrature phase shift keying (QPSK) modulation. The novelty of this…

Information Theory · Computer Science 2019-04-18 Satoshi Takabe , Tadashi Wadayama , Ángeles Vazquez-Castro , Masahito Hayashi

This paper proposes a method for designing error correction codes by combining a known coding scheme with an autoencoder. Specifically, we integrate an LDPC code with a trained autoencoder to develop an error correction code for intractable…

Information Theory · Computer Science 2020-03-03 Eren Balevi , Jeffrey G. Andrews

We present an analysis, under iterative decoding, of coset LDPC codes over GF(q), designed for use over arbitrary discrete-memoryless channels (particularly nonbinary and asymmetric channels). We use a random-coset analysis to produce an…

Information Theory · Computer Science 2007-07-16 Amir Bennatan , David Burshtein