32 citations · 58 across the 37 of their papers we have counts for
6 papers · 1 filter
Spatiotemporal Hyperedges for EEG Seizure Detection and Prediction
Hyunju Kim, Sheo Yon Jhin, Noseong Park +1
Seizure detection and prediction from EEG are clinically important but challenging because seizures are rare, temporally localized, and propagate as coordinated events across multi…
Can Spectral-Clipping Enable Better Learning While Forgetting Less for Low-Rank Adaptation?
Hyowon Wi, Noseong Park
In recent years, low-rank adaptation (LoRA) has emerged as a significant paradigm that freezes pre-trained weights and introduces small, learnable adapters instead of fine-tuning t…
One Sequential Recommendation Model Pretrained from Synthetic Priors Predicts Multiple Datasets
Woosung Kang, Jiwon Jeong, Jonghyeok Shin +2
Existing sequential recommendation models rely on dataset-specific training, where the learned parameters are fitted to the item catalog and the observed interaction distribution o…
How Much Memory Do We Need? Adaptive Memory Gate for Neural Operators
Jihyeon Hur, Yongseok Kwon, Min-Gi Jo +2
Neural operators have emerged as a powerful data-driven approach for solving time-dependent PDEs. Among recent advances, memory-augmented neural operators explicitly incorporate pa…
Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors
Jeongwhan Choi, Jongwoo Kim, Woosung Kang +1
One of the most challenging problems in graph machine learning is generalizing across graphs with diverse properties. Graph neural networks (GNNs) face a fundamental limitation: th…
Graph Signal Processing Meets Mamba2: Adaptive Filter Bank via Delta Modulation
Yehjin Shin, Seojin Kim, Noseong Park
State-space models (SSMs) offer efficient alternatives to attention with linear-time recurrence. Mamba2, a recent SSM-based language model, uses selective input gating and a multi-…