논문 정리

개인적으로 읽고 싶은 논문을 읽고 정리합니다.

Test-Time Adaptation / Generalization

• Sharpness-aware minimization for efficiently improving generalization. In International Conference on Learning Representations, 2021.
  • My Note
• SoTTA: Robust Test-Time Adaptation on Noisy Data Streams. NeurIPS 2023
  • My Note
• Generalization bounds에 대해 이해하기 위한 사전 개념 정리

HCI

Counterfactual(CF) evaluation

Wearable HCI

• Engineering digital biomarkers of interstitial glucose from noninvasive. Bent et al., npj Digital Health, 2021

  • My Note
  • My Code
  • CGM&Wearable Dataset

• "My blood sugar is higher on the weekends": Finding a Role for Context and Context-Awareness in the Design of Health Self-Management Technology. Shriti Raj, Kelsey Toporski.

  • My Note

• Digital health application integrating wearable data and behavioral patterns improves metabolic health. Ashkan Dehghani Zahedani, Tracey McLaughlin.

  • My Note

• 참고 : ETRI 비침습 연속혈당 모니터링 기술동향 - 2021.10.01

• Comparative Efficacy of Commercial Wearables for Circadian Rhythm Home Monitoring from Activity, Heart Rate, and Core Body Temperature. Fan Wu, Patrick Langer.

• Data quality evaluation in wearable monitoring. Sebastian Böttcher, Solveig Vieluf

Mobile HCI

• Knocker

Else

• ESM: Reed Larson and Mihaly Csikszentmihalyi. 2014. The Experience Sampling Method. Springer Netherlands, Dordrecht, 21–34. https://doi.org/10.1007/978-94-017-9088-8_2

논문 서치

• Nature digital medicine articles
• 2024 CHI Best Papers
• 2023 CHI Best Papers
• Ashkan Dehghani Zahedani - January AI

관심

HCI

• Engineering digital biomarkers of interstitial glucose from noninvasive smartwatches: https://www.nature.com/articles/s41746-021-00465-w
• Model Identification with Incomplete Input Data in Type 1 Diabetes: https://www.sciencedirect.com/science/article/pii/S2405896323006547?via%3Dihub
• A Deep Learning Approach for Sleep-Wake Detection from HRV and Accelerometer Data(IEEE EMBS): https://ieeexplore.ieee.org/abstract/document/8834502
• OpenSense: A Platform for Multimodal Data Acquisition and Behavior Perception: https://dl.acm.org/doi/10.1145/3382507.3418832
• Deploying a robotic positive psychology coach to improve college students’ psychological well-being: https://link.springer.com/article/10.1007/s11257-022-09337-8
• Learning to Predict Human Stress Level with Incomplete Sensor Data from Wearable Devices: https://dl.acm.org/doi/10.1145/3357384.3357831
• From wearable sensor data to digital biomarker development: ten lessons learned and a framework proposal: https://www.nature.com/articles/s41746-024-01151-3
• i'sFree: Eyes-Free Gesture Typing via a Touch-Enabled Remote Control(CHI-2019-Google LLC): https://dl.acm.org/doi/pdf/10.1145/3290605.3300678
• Enabling Conversational Interaction with Mobile UI using Large Language Models (MobileHCI-LLM): https://dl.acm.org/doi/10.1145/3544548.3580895
• MentalLLM: https://dl.acm.org/doi/10.1145/3643540

TimeSeries

• ConvTran: Improving Position Encoding of Transformers for Multivariate Time Series Classification: https://link.springer.com/content/pdf/10.1007/s10618-023-00948-2.pdf
• TSLANet: Rethinking Transformers for Time Series Representation Learning, ICML: https://arxiv.org/pdf/2404.08472.pdf
• A Transformer-based Framework for Multivariate Time Series Representation Learning. George Zerveas, Srideepika Jayaraman : https://arxiv.org/abs/2010.02803
  • https://github.com/gzerveas/mvts_transformer
• SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention. Romain Ilbert, Ambroise Odonnat. ICML'24 : https://arxiv.org/abs/2402.10198
  • https://github.com/romilbert/samformer.git

DeepLearning

• Generalization bounds for deep learning: https://arxiv.org/pdf/2012.04115.pdf

MachineLearning

• KAN: Kolmogorov–Arnold Networks: https://arxiv.org/pdf/2404.19756