publications

publications by categories in reversed chronological order. generated by jekyll-scholar.

2023

  1. Channel Vision Transformers: An Image Is Worth C x 16 x 16 Words
    Yujia Bao, Srinivasan Sivanandan, and Theofanis Karaletsos
    Preprint 2023
  2. Contextual Vision Transformers for Robust Representation Learning
    Yujia Bao, and Theofanis Karaletsos
    Preprint 2023

2022

  1. Learning to Split for Automatic Bias Detection
    Yujia Bao, and Regina Barzilay
    Preprint 2022
  2. Learning Stable Classifiers by Transferring Unstable Features
    Yujia Bao, Shiyu Chang, and Regina Barzilay
    In International Conference on Machine Learning 2022

2021

  1. Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
    Yujia Bao, Shiyu Chang, and Regina Barzilay
    In International Conference on Machine Learning 2021
  2. Disease spectrum of gastric cancer susceptibility genes
    Sophia K McKinley, Preeti Singh, Kanhua Yin, Jin Wang, Jingan Zhou, Yujia Bao, Menghua Wu, Kush Pathak, John T Mullen, Danielle Braun, and Kevin S Hughes
    Medical Oncology 2021
  3. Non-medullary thyroid cancer susceptibility genes: evidence and disease spectrum
    Jingan Zhou, Preeti Singh, Kanhua Yin, Jin Wang, Yujia Bao, Menghua Wu, Kush Pathak, Sophia K McKinley, Danielle Braun, Carrie C Lubitz, and Kevin S Hughes
    Annals of Surgical Oncology 2021
  4. Disease spectrum of breast cancer susceptibility genes
    Jin Wang, Preeti Singh, Kanhua Yin, Jingan Zhou, Yujia Bao, Menghua Wu, Kush Pathak, Sophia K McKinley, Danielle Braun, and Kevin S Hughes
    Frontiers in Oncology 2021

2020

  1. Few-shot Text Classification with Distributional Signatures
    Yujia Bao*, Menghua Wu*, Shiyu Chang, and Regina Barzilay
    In International Conference on Learning Representations 2020
  2. Natural language processing to facilitate breast cancer research and management
    Kevin S. Hughes, Jingan Zhou, Yujia Bao, Preeti Singh, Jin Wang, and Kanhua Yin
    The Breast Journal 2020

2019

  1. Validation of a Semiautomated Natural Language Processingā€“Based Procedure for Meta-Analysis of Cancer Susceptibility Gene Penetrance
    Zhengyi Deng*, Kanhua Yin*, Yujia Bao, Victor Diego Armengol, Cathy Wang, Ankur Tiwari, Regina Barzilay, Giovanni Parmigiani, Danielle Braun, and Kevin S. Hughes
    JCO Clinical Cancer Informatics 2019
  2. Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes
    Yujia Bao*, Zhengyi Deng*, Yan Wang, Heeyoon Kim, Victor Diego Armengol, Francisco Acevedo, Nofal Ouardaoui, Cathy Wang, Giovanni Parmigiani, Regina Barzilay, Danielle Braun, and Kevin S Hughes
    JCO Clinical Cancer Informatics 2019
  3. A Machine-Learning Based Drug Repurposing Approach Using Baseline Regularization
    Zhaobin Kuang, Yujia Bao, James Thomson, Michael Caldwell, Peggy Peissig, Ron Stewart, Rebecca Willett, and David Page
    Invited book chapter, In Silico Methods for Drug Repurposing: Methods and Protocols, Springer 2019

2018

  1. Deriving Machine Attention from Human Rationales
    Yujia Bao, Shiyu Chang, Mo Yu, and Regina Barzilay
    In Empirical Methods in Natural Language Processing 2018

2017

  1. Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data
    Yujia Bao, Zhaobin Kuang, Peggy Peissig, David Page, and Rebecca Willett
    In Machine Learning for Healthcare Conference 2017

2016

  1. Rank Revealing Algorithms and their Applications
    Yujia Bao
    Bachelor Thesis, Shanghai Jiao Tong University, 2016