most citedDemonstrating the Efficacy of Kolmogorov-Arnold Networks in Vision Tasks

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

collaborators

5 papers

physics.ao-ph2026

Rescene: band-limited stochastic forcing turns a frozen neural weather operator into a climate emulator

Minjong Cheon

Over the past few years, the rapid development of machine learning (ML) models for weather forecasting has produced deterministic models whose medium-range skill matches or exceeds…

cs.LG2026

Beyond Linear Superposition: Discovering Climate Features in AI Weather Models with KAN-SAE

Minjong Cheon

Deep learning weather prediction models achieve remarkable predictive skill yet remain largely opaque: we know little about how they represent physical climate phenomena internally…

cs.LG2026

KAN-CL: Per-Knot Importance Regularization for Continual Learning with Kolmogorov-Arnold Networks

Minjong Cheon

Catastrophic forgetting remains the central obstacle in continual learning (CL): parameters shared across tasks interfere with one another, and existing regularization methods such…

cs.CV202412 cited

Demonstrating the Efficacy of Kolmogorov-Arnold Networks in Vision Tasks

Minjong Cheon

In the realm of deep learning, the Kolmogorov-Arnold Network (KAN) has emerged as a potential alternative to multilayer projections (MLPs). However, its applicability to vision tas…

cs.CV2024

Kolmogorov-Arnold Network for Satellite Image Classification in Remote Sensing

Minjong Cheon

In this research, we propose the first approach for integrating the Kolmogorov-Arnold Network (KAN) with various pre-trained Convolutional Neural Network (CNN) models for remote se…