Results 51 to 60 of about 7,202 (166)
Improving Token-Based Object Detection With Video
IEEE AccessThis paper improves upon the Pix2Seq object detector by extending it for videos. In the process, it introduces a new way to perform end-to-end video object detection that improves upon existing video detectors in two key ways.
Abhineet Singh, Nilanjan Ray
doaj +1 more source
Minimally Biased Nonparametric Regression and Autoregression
Revstat Statistical Journal, 2008 A nonparametric regression estimator is introduced which adapts to the smoothness of the unknown function being estimated. This property allows the new estimator to automatically achieve minimal bias over a large class of locally smooth functions ...
Timothy L. McMurry +1 more
doaj +1 more source
Autoregressive Energy Machines
CoRR, 2019 Neural density estimators are flexible families of parametric models which have seen widespread use in unsupervised machine learning in recent years. Maximum-likelihood training typically dictates that these models be constrained to specify an explicit density.
Conor Durkan, Charlie Nash
openaire +3 more sources
Autoregressive Conditional Kurtosis [PDF]
Journal of Financial Econometrics, 2005 This article proposes a new model for autoregressive conditional heteroscedasticity and kurtosis. Via a time-varying degrees of freedom parameter, the conditional variance and conditional kurtosis are permitted to evolve separately. The model uses only the standard Student’s t-density and consequently can be estimated simply using maximum likelihood ...
Brooks, Chris +3 more
openaire +2 more sources
Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting
Energies, 2018 We conduct an extensive empirical study on the selection of calibration windows for day-ahead electricity price forecasting, which involves six year-long datasets from three major power markets and four autoregressive expert models fitted either to raw ...
Grzegorz Marcjasz +2 more
doaj +1 more source
Real-time ocean wave prediction in time domain with autoregression and echo state networks
Frontiers in Marine ScienceThis study evaluates the potential of applying echo state networks (ESN) and autoregression (AR) for dynamic time series prediction of free surface elevation for use in wave energy converters (WECs).
Karoline Holand, Henrik Kalisch
doaj +1 more source
Jurnal Economia, 2018 Abstrak: Kejutan Transmisi Kebijakan Moneter dan Variabel Makro Ekonomi di Indonesia: Suatu Pendekatan Structural Vector Autoregression. Tujuan dari tulisan ini adalah untuk mengetahui berapa besar guncangan transmisi kebijakan moneter mempengaruhi ...
Rizal Rahman H. Teapon +1 more
doaj +1 more source
Marrying Autoregressive Transformer and Diffusion with Multi-Reference Autoregression
CoRRWe introduce TransDiff, the first image generation model that marries Autoregressive (AR) Transformer with diffusion models. In this joint modeling framework, TransDiff encodes labels and images into high-level semantic features and employs a diffusion model to estimate the distribution of image samples.
Zhen, Dingcheng +8 more
openaire +3 more sources
Bayesian Compressed Vector Autoregression for Financial Time-Series Analysis and Forecasting
IEEE Access, 2019 Advanced time series models have been intensively developed and used to predict in financial data such as foreign exchange data (forex). In this paper, we implement the random compression method to reduce a large dimensional forex data into much smaller ...
Paponpat Taveeapiradeecharoen +2 more
doaj +1 more source
CoRRAutoRegressive (AR) models have demonstrated competitive performance in image generation, achieving results comparable to those of diffusion models. However, their token-by-token image generation mechanism remains computationally intensive and existing solutions such as VAR often lead to limited sample diversity.
Hongyu Wu +3 more
openaire +3 more sources