Results 81 to 90 of about 1,257,085 (204)
Context‑Aware Image Restoration Based on Fused Semantic Information
Shuju Caiji Yu ChuliIn recent years， generative adversarial networks have been widely used in the field of image restoration and have achieved good results. However， current methods do not consider problems of blurred structures and textures in high-resolution images （512 ...
ZU Yi, ZHANG Sunjie, WU Peng, MA Yueheng
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HGCA: Hybrid GPU-CPU Attention for Long Context LLM Inference
Scaling inference for large language models (LLMs) is increasingly constrained by limited GPU memory, especially due to growing key-value (KV) caches required for long-context generation. While existing approaches offload KV caches to CPU memory or apply sparse attention to reduce GPU load, they often underutilize CPU compute resources and compromise ...
Deng, Weishu +8 more
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A Review of State of the Art Deep Learning Models for Ontology Construction
IEEE AccessResearchers are working towards automation of ontology construction to manage the ever-growing data on the web. Currently, there is a shift from the use of machine learning techniques towards exploration of deep learning models for ontology construction.
Tsitsi Zengeya +1 more
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Seasonal dynamic factor analysis and bootstrap inference : application to electricity market forecasting [PDF]
Year-ahead forecasting of electricity prices is an important issue in the current context of electricity markets. Nevertheless, only one-day-ahead forecasting is commonly tackled up in previous published works.
andrés M. Alonso +3 more
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Speed of Adjustment in Cointegrated Systems [PDF]
This paper considers the speed of adjustment to long-run equilibria, in the context of cointegrated Vector Autoregressive Processes (VAR). We discuss the definition of multivariate p-lives for any indicator of predictive ability, concentrating on ...
Fanelli, Luca, Paruolo, Paolo
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World Electric Vehicle JournalBattery state-of-health (SoH) estimation is central to transportation electrification because it conditions safety limits, warranty accounting, power capability management, and long-horizon fleet optimization.
Kumbirayi Nyachionjeka +1 more
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Writing in the Margins: Better Inference Pattern for Long Context Retrieval
In this paper, we introduce Writing in the Margins (WiM), a new inference pattern for Large Language Models designed to optimize the handling of long input sequences in retrieval-oriented tasks. This approach leverages the chunked prefill of the key-value cache to perform segment-wise inference, which enables efficient processing of extensive contexts ...
Russak, Melisa +6 more
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Applied SciencesIn recent years, a growing number of real-time semantic segmentation networks have been developed to improve segmentation accuracy. However, these advancements often come at the cost of increased computational complexity, which limits their inference ...
Jia Tian +4 more
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PLoS Computational BiologyWild populations are increasingly threatened by human-mediated climate change and land use changes. As populations decline, the probability of inbreeding increases, along with the potential for negative effects on individual fitness.
Gabriel A A Silva +4 more
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Optimized Predictive Coverage by Averaging Time‐Windowed Bayesian Distributions
Water Resources ResearchHydrogeological models require reliable uncertainty intervals that honestly reflect the total uncertainties of model predictions. The operation of a conventional Bayesian framework only produces realistic (interpretable in the context of the natural ...
Han‐Fang Hsueh +3 more
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