12 papers · ranked by Valyu relevance
Haochu Ku, Kunpeng Zhang, Xiangge He, Min Zhang + 2 more
'Vittorio M. N. Passaro'] Flow characteristic monitoring includes parameters such as flow regime, fluid characteristic frequency, and flow rate, which are crucial for optimizing production and ensuring the safety of oil and gas transportation systems. Existing fluid monitoring technologies, such as various flow meters…
Tiago de Souza Farias, Jonas Maziero
Reversibility in artificial neural networks allows us to retrieve the input given an output. We present feature alignment, a method for approximating reversibility in arbitrary neural networks. We train a network by minimizing the distance between the output of a data point and the random output with respect to a…
Tatsuaki Wada, Antonio Maria Scarfone
We consider Onsager’s non-equilibrium thermodynamics from the perspective of the gradient flow in information geometry. Assuming Onsager’s reciprocal relations, we can regard his phenomenological equations as gradient-flow equations and develop two different gradient-flow models. We consider their features and their…
Yuhang Wang, Weihua Chen, Linjing Song, Zhiping Xu + 6 more
With the rapid growth of data volume in sensor networks, lossy source coding systems achieve high-efficiency data compression with low distortion under limited transmission bandwidth. However, conventional compression algorithms rely on a two-stage framework with high computational complexity and frequently struggle to…
Pengxi Fu, Zhen Wang, Jianxin Guo, Yushuai Zhang + 4 more
Modern communication systems increasingly leverage multiple information streams-including channel observations, statistical models, and contextual knowledge-to enhance decoding reliability. However, the varying and often unpredictable quality of these sources poses a critical challenge: rigid combination rules fail…
Wei Huang, Zhuowei Wang, Xiaobo Liu, Dayu Zhu + 2 more
'Leixiang Wu'] Flow reduction has greatly affected the river ecological systems, and it has attracted much attention. However, less attention has been paid to response to flow restoration, especially flow restoration in gradient. Flow regime of rivers may affect river functional indicators and microbial community…
Alexander Muacevic, John R Adler, Marina Leitman, Mohameed Daoud + 2 more
'Vladimir Tyomkin' 'Shmuel Fuchs'] Purpose: The decision to assess the severity and determine the ideal timing of intervention for low-gradient aortic stenosis poses a greater challenge. Recently, a novel method for determining the flow status of patients with aortic stenosis has been introduced, utilizing flow rate…
Guillaume Quétant, Yury Belousov, Vitaliy Kinakh, Slava Voloshynovskiy + 2 more
'Slava Voloshynovskiy' 'Sotiris Kotsiantis' 'Marco Piangerelli'] We present a novel information-theoretic framework, termed as TURBO, designed to systematically analyse and generalise auto-encoding methods. We start by examining the principles of information bottleneck and bottleneck-based networks in the auto-encoding…
Viktoria Schuster, Anders Krogh, Fabio Aiolli, Mirko Polato
Autoencoders are commonly used in representation learning. They consist of an encoder and a decoder, which provide a straightforward method to map n-dimensional data in input space to a lower m-dimensional representation space and back. The decoder itself defines an m-dimensional manifold in input space. Inspired by…
Lokien X. van Nunen, Peter Damman
That functional testing to assess the haemodynamic significance of a particular coronary artery stenosis is superior to solely visual assessment is indisputable when making decisions regarding revascularisation. In past decades, both fractional flow reserve (FFR) and coronary flow reserve (CFR) have emerged as two…
Alireza Tasdighi, Mansoor Yousefi, Jun Chen
Weighted belief propagation (WBP) for the decoding of linear block codes is considered. In WBP, the Tanner graph of the code is unrolled with respect to the iterations of the belief propagation decoder. Then, weights are assigned to the edges of the resulting recurrent network and optimized offline using a training…
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…