About me

I’m a Ph.D student at Machine Learning and Artificial Intelligence (MLAI) lab in KAIST, under the supervision of Prof. Sung Ju Hwang. I finished my B.S. degree at UNIST in 2016, and M.S. degree at UNIST in 2018 under the supervision of Prof. Sung Ju Hwang.

My research interest includes:

  • Meta-learning
  • Bayesian deep learning with variational inference
  • Understanding and modeling uncertainty in deep learning
  • Learning with noise and perturbation

Awards

  • Google AI Focused Research Awards Program, 2018-2019
  • Global Ph.D Fellowship Program, 2019-2021

Preprints

  • Transductive Few-shot Learning with Meta-Learned Confidence

    [paper]
    Sung Min Kye, Hae Beom Lee, Hoirin Kim, Sung Ju Hwang
    arXiv, 2020

  • Adaptive Network Sparsification with Dependent Variational Beta-Bernoulli Dropout

    [paper]
    Juho Lee, Saehoon Kim, Jaehong Yoon, Hae Beom Lee, Eunho Yang, Sung Ju Hwang
    arXiv, 2018

Conference Publications

  • Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks

    [paper] [code]
    Hae Beom Lee*, Hayeon Lee*, Donghyun Na*, Saehoon Kim, Minseop Park, Eunho Yang, Sung Ju Hwang
    (*: equal contribution)
    ICLR 2020, Oral Presentation (48/2594=1.9%)

  • Meta Dropout: Learning to Perturb Latent Features for Generalization

    [paper] [code]
    Hae Beom Lee, Taewook Nam, Eunho Yang, Sung Ju Hwang
    ICLR 2020

  • DropMax: Adaptive Variational Softmax

    [paper][code]
    Hae Beom Lee, Juho Lee, Saehoon Kim, Eunho Yang, Sung Ju Hwang
    NeurIPS 2018

  • Uncertainty-Aware Attention for Reliable Interpretation and Prediction

    [paper][code]
    Jay Heo*, Hae Beom Lee*, Saehoon Kim, Juho Lee, Kwang Joon Kim, Eunho Yang, Sung Ju Hwang
    (*: equal contribution)
    NeurIPS 2018

  • Deep Asymmetric Multi-task Feature Learning

    [paper][code]
    Hae Beom Lee, Eunho Yang, Sung Ju Hwang
    ICML 2018