1 citations · 1 across the 3 of their papers we have counts for
4 papers
Discretizing Continuous Time Series for Imputation with Masked Diffusion Training
Dongbin Kim, Seungyun Lee, Geonwoo Shin +1
Time series imputation is a crucial area for reliable time series analysis, yet it remains challenging due to the complex temporal dynamics and noise of real-world data. Existing a…
BayesNAM: Leveraging Inconsistency for Reliable Explanations
Hoki Kim, Jinseong Park, Yujin Choi +2
Neural additive model (NAM) is a recently proposed explainable artificial intelligence (XAI) method that utilizes neural network-based architectures. Given the advantages of neural…
TimeBridge: Better Diffusion Prior Design with Bridge Models for Time Series Generation
Jinseong Park, Seungyun Lee, Woojin Jeong +2
Time series generation is widely used in real-world applications such as simulation, data augmentation, and hypothesis testing. Recently, diffusion models have emerged as the de fa…
Impact of EIP-4844 on Ethereum: Consensus Security, Ethereum Usage, Rollup Transaction Dynamics, and Blob Gas Fee Markets
Seongwan Park, Bosul Mun, Seungyun Lee +4
On March 13, 2024, Ethereum implemented EIP-4844, designed to enhance its role as a data availability layer. While this upgrade reduces data posting costs for rollups, it also rais…