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Found 5 papers, 2 papers with code
Evaluating Text-to-Image Generative Models: An Empirical Study on Human Image Synthesis
In this paper, we present an empirical study introducing a nuanced evaluation framework for text-to-image (T2I) generative models, applied to human image synthesis.
FrAug: Frequency Domain Augmentation for Time Series Forecasting
In time series forecasting (TSF), we need to model the fine-grained temporal relationship within time series segments to generate accurate forecasting results given data in a look-back window.
An Empirical Study on the Efficacy of Deep Active Learning for Image Classification
Third, performing data selection in the SSAL setting can achieve a significant and consistent performance improvement, especially with abundant unlabeled data.
Are Transformers Effective for Time Series Forecasting?
Recently, there has been a surge of Transformer-based solutions for the long-term time series forecasting (LTSF) task.
Ranked #1 on
Time Series Forecasting
on ETTh1 (96) Univariate
SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction
One unique property of time series is that the temporal relations are largely preserved after downsampling into two sub-sequences.
Ranked #1 on
Time Series Forecasting
on ETTh1 (24) Multivariate
(using extra training data)
