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researcher

Kun Yi

4 papers hereh-index 121.1k citations23 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG4
same name
  • Kun Yi — 8 papers
  • Kun Yi — 3 papers, h 8
  • Kun Yi — 2 papers, h 1
  • Kun Yi — 1 paper, h 4
  • Kun Yi — 1 paper, h 1
  • Kun Yi — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedFilterNet: Harnessing Frequency Filters for Time Series Forecasting

12 citations · 12 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2025

Improving Prediction Certainty Estimation for Reliable Early Exiting via Null Space Projection

Jianing He, Qi Zhang, Duoqian Miao +4

Early exiting has demonstrated great potential in accelerating the inference of pre-trained language models (PLMs) by enabling easy samples to exit at shallow layers, eliminating t…

cs.LG2025

Amplifier: Bringing Attention to Neglected Low-Energy Components in Time Series Forecasting

Jingru Fei, Kun Yi, Wei Fan +2

We propose an energy amplification technique to address the issue that existing models easily overlook low-energy components in time series forecasting. This technique comprises an…

cs.LG2025

MedGNN: Towards Multi-resolution Spatiotemporal Graph Learning for Medical Time Series Classification

Wei Fan, Jingru Fei, Dingyu Guo +5

Medical time series has been playing a vital role in real-world healthcare systems as valuable information in monitoring health conditions of patients. Accurate classification for…

cs.LG2024★ 12 cited

FilterNet: Harnessing Frequency Filters for Time Series Forecasting

Kun Yi, Jingru Fei, Qi Zhang +4

While numerous forecasters have been proposed using different network architectures, the Transformer-based models have state-of-the-art performance in time series forecasting. Howe…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.