25 papers · ranked by Valyu relevance
Martin Rosvall, Carl T. Bergstrom, Fabio Rapallo
To comprehend the hierarchical organization of large integrated systems, we introduce the hierarchical map equation, which reveals multilevel structures in networks. In this information-theoretic approach, we exploit the duality between compression and pattern detection; by compressing a description of a random walker…
Xin Liang, Ben Whitney, Jieyang Chen, Lipeng Wan + 7 more
'Dingwen Tao' 'James Kress' 'David Pugmire' 'Matthew Wolf' 'Norbert Podhorszki' 'Scott Klasky'] Abstract—Data management is becoming increasingly important in dealing with the large amounts of data produced by today's large-scale scientific simulations and instruments. Existing multilevel compression algorithms offer a…
Chaohua Yang, Baoqing Yu, Fenfen Ma, Huiping Lu + 5 more
'Qinghua You' 'Bin Yu' 'Jianlan Qiao' 'Jianjun Feng'] Background In recent years, multilevel spinal cord injuries (SCIs) have gained a substantial amount of attention from clinicians and researchers. Multilevel noncontinuous SCI patients cannot undergo the multiple steps of a one-stage operation because of a poor…
Wang, Daoce, Grosset, Pascal + 17 more
Error-bounded lossy compression is one of the most efficient solutions to reduce the volume of scientific data. For lossy compression, progressive decompression and random-access decompression are critical features that enable on-demand data access and flexible analysis workflows. However, these features can severely…
Chen-Hsiu Huang, Ja-Ling Wu, Jun Chen
End-to-end learned image compression codecs have notably emerged in recent years. These codecs have demonstrated superiority over conventional methods, showcasing remarkable flexibility and adaptability across diverse data domains while supporting new distortion losses. Despite challenges such as computational…
Pumiao Yan, Dante G. Muratore, E.J. Chichilnisky, Boris Murmann + 1 more
Scaling neural recording systems to thousands of channels creates extreme bandwidth demands, posing a challenge for resource-constrained, implantable devices. This work introduces an adaptive, multi-stage compression framework for high-bandwidth neural interfaces. The system combines a Wired-OR analog-to-digital…
Anders Andreasen, Maria Bonto, Fernando Montero
– This paper presents a framework for optimisation and techno-economic analysis of various pressurisation pathways for CO2 pipeline transportation. The pressurisation pathways include a conventional compression only case from initial to final pressure, a sub-critical compression part followed by cooling, liquefaction…
Gangtao Xin, Pingyi Fan, Amelia Carolina Sparavigna, Armando J. Pinho
'Armando J. Pinho'] Soft compression is a lossless image compression method that is committed to eliminating coding redundancy and spatial redundancy simultaneously. To do so, it adopts shapes to encode an image. In this paper, we propose a compressible indicator function with regard to images, which gives a threshold…
Jérémy Aghaei Mazaheri, Elif Vural, Claude Labit, Christine Guillemot
'Christine Guillemot'] Abstract—Sparse representations using overcomplete dictionaries have proved to be a powerful tool in many signal processing applications such as denoising, super-resolution, inpainting, compression or classification. The sparsity of the representation very much depends on how well the dictionary…
Tejasvee Bisen, Muhammad Faisal Javed, Shashank Kirtania, P. Nagabhushan
'P. Nagabhushan'] Abstract—For any digital application with document images such as retrieval, the classification of document images becomes an essential stage. Conventionally for the purpose, the full versions of the documents, that is the uncompressed document images make the input dataset, which poses a threat due…
Runzhao Yang, Tingxiong Xiao, Yuxiao Cheng, Anan Li + 7 more
Efficient storage and sharing of massive biomedical data would open up their wide accessibility to different institutions and disciplines. However, compressors tailored for natural photos/videos are rapidly limited for biomedical data, while emerging deep learning based methods demand huge training data and are…
Axel Trefzer, Alexandros Stamatakis
Bayesian Markov-Chain Monte Carlo (MCMC) methods for phylogenetic tree inference, that is, inference of the evolutionary history of distinct species using their molecular sequence data, typically generate large sets of phylogenetic trees. The trees generated by the MCMC procedure are samples of the posterior…
Xianzhi Zeng, Shuhao Zhang
—In the burgeoning realm of Internet of Things (IoT) applications on edge devices, data stream compression has become increasingly pertinent. The integration of added compression overhead and limited hardware resources on these devices calls for a nuanced software-hardware co-design. This paper introduces CStream, a…
Yifan Ma, Chengqiang Yi, Yao Zhou, Zhaofei Wang + 9 more
With the rapid development in advanced imaging techniques, massive image data have been acquired for various biomedical applications, posing significant challenges to their efficient storage, transmission, and sharing. Classical model-or learning-based compression algorithms are optimized for specific dimensional data…
Max Ehrlich
| Title of Dissertation: | The First Principles of Deep Learning and Compression | | --- | --- | | | Max Ehrlich | | | Doctor of Philosophy, 2022 | | Dissertation Directed By: | Professor Abhinav Shrivastava | | | Department of Computer Science | | | Professor Larry S. Davis | | | Department of Computer Science |
Dohyeon Lee, Juyeon Park, Juheon Lee, Chungha Lee + 2 more
Holotomography (HT) is a label-free, three-dimensional quantitative phase imaging technique that captures refractive index distributions of biological samples at sub-micron resolution. As modern HT systems enable high-throughput and large-scale acquisition, they produce terabyte-scale datasets that require efficient…
Authors not listed
Cost effective and reliable hydrogen compression remains a challenging barrier in the wide-spread adoption of hydrogen as an energy carrier. The prevailing technology of mechanical compression suffers from several drawbacks, some of which can be addressed by non-mechanical compression strategies (e.g., electrochemical…
Cristian Peñaranda, Carlos Reaño, Federico Silla, David Plets
GPUs are commonly used to accelerate the execution of applications in domains such as deep learning. Deep learning applications are applied to an increasing variety of scenarios, with edge computing being one of them. However, edge devices present severe computing power and energy limitations. In this context, the use…
Conner S. Philson, Julien G. A. Martin, Daniel T. Blumstein
The degree to which phenotypes are shaped by multilevel selection – the theoretical framework proposing natural selection occurs at more than one level of biological organisation – is a classic debate in biology. Though social behaviours are a common theoretical example for multilevel selection, it is unknown if and…
Sergey Usoltsev, Oleg Raitman, Alexander Shokurov, Yuriy Marfin
Associative behavior of geometrically anisotropic meso-(4-octadecyloxy-phenyl)-boron-dipyrrin (BODIPY) studied spectroscopically in binary solvent mixtures and upon compression in Langmuir floating layers. Different steady and excited state species were found upon monolayer compression and facilitated aggregation in…
Daniel Probst
Last year, a preprint gained notoriety, proposing that a k-nearest neighbour classifier is able to outperform large-language models using compressed text as input and normalised compression distance (NCD) as a metric. In chemistry and biochemistry, molecules are often represented as strings, such as SMILES for small…
M Baritha Begum, N. Deepa, Mueen Uddin, Rajesh Kaluri + 2 more
'Maha Abdelhaq' 'Raed Alsaqour'] Data stored on physical storage devices and transmitted over communication channels often have a lot of redundant information, which can be reduced through compression techniques to conserve space and reduce the time it takes to transmit the data. The need for adequate security…
Giacomo Chiarot, Claudio Silvestri
Smart objects are increasingly widespread and their ecosystem, also known as the Internet of Things, is relevant in many application scenarios. The huge amount of temporally annotated data produced by these smart devices demands efficient techniques for the transfer and storage of time series data. Compression…
jeff smith, R. Fredrik Inglis
In the evolution of social interactions among microbes, mathematical theory can aid empirical research but is often only used heuristically. How to properly formulate social evolution theory has also been contentious. Here we evaluate kin and multilevel selection theory as tools for analyzing microbial data. We…
Sung Sakong, Axel Groß, R. Jürgen Behm
As an example for bimetallic surfaces in general, we have systematically investigated the thermodynamic surface properties of bimetallic Ag/Pt(111) and Ag/Pd(111) surfaces, including pseudomorphic Ag film covered surfaces and M1Ag3/M(111) (M = Pt, Pd) monolayer surface alloys, by periodic density functional theory…