We, LRNING (pronounced as "learning"), study deep learning.

• • Representation Learning (Feature Learning, Self-Supervised Learning, ...)

  • Optimization and Generalization (Neural Network Training Dynamics, Implicit Bias, Sharpness, ...)

  • Distribution Shift (Robustness, Test-Time Adaptation, ...)

  • Trustworthy AI (LLM Hallucination, Adversarial Robustness, Privacy-Preserving ML, ...)

  • Transformers (Efficient Transformers, In-Context Learning, ...)

  • Generative Models (Diffusion Models, ...)

  • ...

If you are interested in joining our group, please send an email to me with a short CV (e.g. research interests, future goals, achievements, etc.) and arrange an interview. We highly recommend contacting us as quickly as possible.

 
연구실에 관심이 있으시다면, 간단한 CV(관심 주제 - 가능하면 위 리스트 중에서, 목표 등)와 함께 메일주시기 바랍니다. 학부 인턴 등 가능하면 일찍 면담하는 것을 추천합니다.
(학부인턴 상시 모집)

Members