Results 11 to 20 of about 12,987,723 (342)
Japanese Journal of Statistics and Data Science, 2019 AbstractWe discuss developments and future prospects for statistical modeling and inference for spatial data that have long memory. While a number of contributons have been made, the literature is relatively small and scattered, compared to the literatures on long memory time series on the one hand, and spatial data with short memory on the other. Thus,
P. Robinson
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TALLFormer: Temporal Action Localization with Long-memory Transformer [PDF]
European Conference on Computer Vision, 2022 Most modern approaches in temporal action localization divide this problem into two parts: (i) short-term feature extraction and (ii) long-range temporal boundary localization.
Feng Cheng, Gedas Bertasius
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MovieChat: From Dense Token to Sparse Memory for Long Video Understanding [PDF]
Computer Vision and Pattern Recognition, 2023 Recently, integrating video foundation models and large language models to build a video understanding system can overcome the limitations of specific pre-defined vision tasks. Yet, existing systems can only handle videos with very few frames.
Enxin Song +10 more
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XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model [PDF]
European Conference on Computer Vision, 2022 We present XMem, a video object segmentation architecture for long videos with unified feature memory stores inspired by the Atkinson-Shiffrin memory model. Prior work on video object segmentation typically only uses one type of feature memory.
Ho Kei Cheng, A. Schwing
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MemoryBank: Enhancing Large Language Models with Long-Term Memory [PDF]
AAAI Conference on Artificial Intelligence, 2023 Large Language Models (LLMs) have drastically reshaped our interactions with artificial intelligence (AI) systems, showcasing impressive performance across an extensive array of tasks.
Wanjun Zhong +4 more
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Augmenting Language Models with Long-Term Memory [PDF]
Neural Information Processing Systems, 2023 Existing large language models (LLMs) can only afford fix-sized inputs due to the input length limit, preventing them from utilizing rich long-context information from past inputs.
Weizhi Wang +6 more
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Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting [PDF]
AAAI Conference on Artificial Intelligence, 2020 Many real-world applications require the prediction of long sequence time-series, such as electricity consumption planning. Long sequence time-series forecasting (LSTF) demands a high prediction capacity of the model, which is the ability to capture ...
Haoyi Zhou +6 more
semanticscholar +1 more source
Temperature Anomalies, Long Memory, and Aggregation
Econometrics, 2021 Econometric studies for global heating have typically used regional or global temperature averages to study its long memory properties. One typical explanation behind the long memory properties of temperature averages is cross-sectional aggregation ...
J. E. Vera-Valdés
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Switchbacks in the Near-Sun Magnetic Field: Long Memory and Impact on the Turbulence Cascade [PDF]
Astrophysical Journal Supplement Series, 2019 One of the most striking observations made by Parker Solar Probe during its first solar encounter is the omnipresence of rapid polarity reversals in a magnetic field that is otherwise mostly radial.
T. Dudok de Wit +16 more
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Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks [PDF]
Annual Meeting of the Association for Computational Linguistics, 2015 Because of their superior ability to preserve sequence information over time, Long Short-Term Memory (LSTM) networks, a type of recurrent neural network with a more complex computational unit, have obtained strong results on a variety of sequence ...
Kai Sheng Tai +2 more
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