Results 71 to 80 of about 1,257,085 (204)
A Survey of Location Prediction on Twitter
, 2018 Locations, e.g., countries, states, cities, and point-of-interests, are central to news, emergency events, and people's daily lives. Automatic identification of locations associated with or mentioned in documents has been explored for decades.
Han, Jialong, Sun, Aixin, Zheng, Xin
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Bayesian Workflow for Generative Modeling in Computational Psychiatry
Computational PsychiatryComputational (generative) modelling of behaviour has considerable potential for clinical applications. In order to unlock the potential of generative models, reliable statistical inference is crucial. For this, Bayesian workflow has been suggested which,
Alexander J. Hess +10 more
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Improving Retrieval-Based Question Answering with Deep Inference Models
, 2019 Question answering is one of the most important and difficult applications at the border of information retrieval and natural language processing, especially when we talk about complex science questions which require some form of inference to determine ...
Pirtoaca, George-Sebastian +2 more
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Scientism on Steroids: A Review of Freedom Evolves by Daniel Dennett (2003) (review revised 2019) [PDF]
, 2019 ``People say again and again that philosophy doesn´t really progress, that we are still occupied with the same philosophical problems as were the Greeks. But the people who say this don´t understand why it has to be so.
Starks, Michael
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Seasonal dynamic factor analysis and bootstrap inference : application to electricity market forecasting [PDF]
, 2008 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.
Alonso, Andrés M. +3 more
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A default prior for regression coefficients
, 2018 When the sample size is not too small, M-estimators of regression coefficients are approximately normal and unbiased. This leads to the familiar frequentist inference in terms of normality-based confidence intervals and p-values.
van Zwet, Erik
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Cocktail: Chunk-Adaptive Mixed-Precision Quantization for Long-Context LLM Inference
2025 Design, Automation & Test in Europe Conference (DATE)Accepted by the Design, Automation, and Test in Europe 2025 (DATE 2025)
Tao, Wei +4 more
openaire +2 more sources
Contextual Motifs: Increasing the Utility of Motifs using Contextual Data
, 2017 Motifs are a powerful tool for analyzing physiological waveform data. Standard motif methods, however, ignore important contextual information (e.g., what the patient was doing at the time the data were collected).
Bailey T. L. +9 more
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Data-Driven Optimized Load Forecasting: An LSTM-Based RNN Approach for Smart Grids
IEEE AccessAccurate load forecasting is essential for ensuring the stability and efficiency of modern power systems, particularly in the context of increasing renewable energy integration.
Muhammad Asghar Majeed +3 more
doaj +1 more source
PLoS Computational BiologyWe introduce the inference for populations at risk (iPAR) framework which enables modelling and estimation of spatial disease dynamics in scenarios where the population at risk is unknown or poorly mapped.
Stephen Catterall +2 more
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