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A technique of lossless compression via substring enumeration (CSE) attains compression ratios as well as popular lossless compressors for one-dimensional (1D) sources. The CSE utilizes a probabilistic model built from the circular string…

Information Theory · Computer Science 2017-01-25 Takahiro Ota , Hiroyoshi Morita

In this paper, we study the problem of storing an archive of versioned data in a reliable and efficient manner in distributed storage systems. We propose a new storage technique called differential erasure coding (DEC) where the differences…

Information Theory · Computer Science 2015-03-19 J. Harshan , Anwitaman Datta , Frédérique Oggier

Persistent homology (PH) is a rigorous mathematical theory that provides a robust descriptor of data in the form of persistence diagrams (PDs) which are 2D multisets of points. Their variable size makes them, however, difficult to combine…

Machine Learning · Statistics 2019-06-14 Bartosz Zielinski , Michal Lipinski , Mateusz Juda , Matthias Zeppelzauer , Pawel Dlotko

Certified deletion allows Alice to outsource data to Bob and, at a later time, obtain a verifiable guarantee that the file has been irreversibly deleted at her request. The functionality, while impossible using classical information alone,…

Cryptography and Security · Computer Science 2026-01-21 Kunal Dey , Reihaneh Safavi-Naini

The working mechanisms of complex natural systems tend to abide by concise and profound partial differential equations (PDEs). Methods that directly mine equations from data are called PDE discovery, which reveals consistent physical laws…

Machine Learning · Computer Science 2023-03-17 Mengge Du , Yuntian Chen , Dongxiao Zhang

We propose a general method for semantic representation of images and other data using progressive coding. Semantic coding allows for specific pieces of information to be selectively encoded into a set of measurements that can be highly…

Signal Processing · Electrical Eng. & Systems 2023-09-29 Eva Riherd , Raghu Mudumbai , Weiyu Xu

Neural networks are one tool for approximating non-linear differential equations used in scientific computing tasks such as surrogate modeling, real-time predictions, and optimal control. PDE foundation models utilize neural networks to…

Machine Learning · Computer Science 2025-02-11 Elisa Negrini , Yuxuan Liu , Liu Yang , Stanley J. Osher , Hayden Schaeffer

An implementation-efficient finite alphabet decoder for polar codes relying on coarsely quantized messages and low-complexity operations is proposed. Typically, finite alphabet decoding performs concatenated compression operations on the…

Information Theory · Computer Science 2023-05-29 Philipp Mohr , Syed Aizaz Ali Shah , Gerhard Bauch

There have been growing interests in leveraging experimental measurements to discover the underlying partial differential equations (PDEs) that govern complex physical phenomena. Although past research attempts have achieved great success…

Machine Learning · Computer Science 2023-05-23 Chengping Rao , Pu Ren , Yang Liu , Hao Sun

Monocular depth estimation (MDE) aims to transform an RGB image of a scene into a pixelwise depth map from the same camera view. It is fundamentally ill-posed due to missing information: any single image can have been taken from many…

Computer Vision and Pattern Recognition · Computer Science 2022-05-13 Dylan Auty , Krystian Mikolajczyk

Constrained sequence codes have been widely used in modern communication and data storage systems. Sequences encoded with constrained sequence codes satisfy constraints imposed by the physical channel, hence enabling efficient and reliable…

Information Theory · Computer Science 2018-09-07 Congzhe Cao , Duanshun Li , Ivan Fair

Without careful long-term preservation digital data may be lost to a number of factors, including physical media decay, lack of suitable decoding equipment, and the absence of software. When raw data can be read but lack suitable…

Graphics · Computer Science 2011-12-30 Daniel L. Ruderman

In this work, we present hardware and software implementations of flexible polar systematic encoders and decoders. The proposed implementations operate on polar codes of any length less than a maximum and of any rate. We describe the…

Information Theory · Computer Science 2016-08-29 Gabi Sarkis , Ido Tal , Pascal Giard , Alexander Vardy , Claude Thibeault , Warren J. Gross

This fourth and last tome is focusing on describing the envisioned works for a project that has been presented in the preceding tome. It is about a new approach dedicated to the coding of still and moving pictures, trying to bridge the…

Computer Vision and Pattern Recognition · Computer Science 2020-01-14 Olivier Guye

We propose Parabolic Position Encoding (PaPE), a parabola-based position encoding for vision modalities in attention-based architectures. Given a set of vision tokens-such as from videos, event camera streams, images, or point clouds-our…

Multimodal Large Language Models (MLLMs) struggle with precise reasoning for structured visuals like charts and diagrams, as pixel-based perception lacks a mechanism for verification. To address this, we propose to leverage derendering --…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Junhong Shen , Mu Cai , Bo Hu , Ameet Talwalkar , David A Ross , Cordelia Schmid , Alireza Fathi

Relative position encoding (RPE) is important for transformer to capture sequence ordering of input tokens. General efficacy has been proven in natural language processing. However, in computer vision, its efficacy is not well studied and…

Computer Vision and Pattern Recognition · Computer Science 2021-07-30 Kan Wu , Houwen Peng , Minghao Chen , Jianlong Fu , Hongyang Chao

Positional encoding (PE) underpins how permutation-invariant Transformers represent sequence order, yet how positional information is processed and stored remains poorly understood. Modern PE methods such as RoPE still struggle on tasks…

Computation and Language · Computer Science 2026-05-29 Pierre-Antoine Lequeu , Camille Barboule , Benjamin Piwowarski

The Run Length Encoding (RLE) compression method is a long standing simple lossless compression scheme which is easy to implement and achieves a good compression on input data which contains repeating consecutive symbols. In its pure form…

Data Structures and Algorithms · Computer Science 2021-04-01 Sven Fiergolla , Petra Wolf

Video large language models (Vid-LLMs), which excel in diverse video-language tasks, can be effectively constructed by adapting image-pretrained vision-language models (VLMs). However, this adaptation remains challenging, as it requires…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Yiyang Huang , Yizhou Wang , Yun Fu