/papers_we_read

Summaries of the papers that are discussed by VLG

Deep Learning Paper Summaries

Summaries for papers discussed by VLG.

Summaries

2019

  • Zero-Shot Entity Linking by Reading Entity Descriptions[Paper][Review]
    • Lajanugen Logeswaran , Ming-Wei Chang‡ Kenton Lee , Kristina Toutanova , Jacob Devlin, Honglak Lee ACL-2019
  • Do you know that Florence is packed with visitors? Evaluating state-of-the-art models of speaker commitment. [Paper][Review]
    • Nanjiang Jiang and Marie-Catherine de Marneffe , ACL-2019
  • Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations [Paper][Review]
    • Vincent Sitzmann, Michael Zollhofer, Gordon Wetzstein, NIPS-2019
  • Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in Texts[Paper][Review]
    • Rui Xia, Zixiang Ding, ACL-2019
  • Putting an End to End-to-End: Gradient-Isolated Learning of Representations [Paper][Review]
    • Sindy Lowe, Peter O' Connor, Bastiaan S. Veeling, NIPS-2019
  • Bridging the Gap between Training and Inference for Neural Machine Translation [Paper][Review]
    • Wen Zhang, Yang Feng, Fandong Meng, Di You, Qun Liu, ACL-2019
  • Designing and Interpreting Probes with Control Tasks [Paper][Review]
    • John Hewitt, Percy Liang, EMNLP-2019
  • Specializing Word Embeddings (for Parsing) by Information Bottleneck [Paper][Review]
    • Xiang Lisa Li, Jason Eisner, EMNLP-2019
  • vGraph: A Generative Model for Joint Community Detection and Node Representational Learning [Paper] [Review]
    • Fan-Yun Sun, Meng Qu, Jordan Hoffmann, Chin-Wei Huang, Jian Tang, NIPS-2019
  • Uniform convergence may be unable to explain generalization in deep learning [Paper][Review]
    • Vaishnavh Nagarajan, J. Zico Kolter, NIPS-2019
  • SinGAN: Learning a Generative Model from a Single Natural Image [Paper] [Review]
    • Tamar Rott Shaham, Tali Dekel, Tomer Michaeli, ICCV-2019
  • Graph U-Nets [Paper] [Review]
    • Hongyang Gao, Shuiwang Ji, ICML-2019
  • Feature Denoising for Improving Adversarial Robustness [Paper] [Review]
    • Cihang Xie, Yuxin Wu, Laurens van der Maaten, Alan Yuille, kaiming He, CVPR-2019
  • This Looks Like That: Deep Learning for Interpretable Image Recognition [Paper] [Review]
    • Chaofan Chen, Oscar Li, Chaofan Tao, Alina Jade Barnett, Jonathan Su, Cynthia Rudin, NIPS-2019

2018

  • CyCADA: Cycle-Consistent Adversarial Domain Adaptation [Paper] [Review]
    • Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell, ICML-2018

2017

  • Unpaired Image-to-Image Translation using Cycle Consistent Adversarial Networks [Paper] [Review]
    • Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros, ICCV-2017
  • Densely Connected Convolutional Networks [Paper] [Review]
    • Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger, CVPR-2017

2016

  • Siamese Recurrent Architectures for Learning Sentence Similarity [Paper] [Review]
    • Jonas Mueller, Aditya Thyagarajan, AAAI-2016