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Summaries of *some* of the machine learning paper, I read
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ML Research-Paper Summary Blog

Welcome to my paper summary blog! These are some of the papers that I found really interesting but not a summary explaining them around, so I wrote one. If you find any issue with points that I made, feel free to reach out to me or send a pull request.


  • Dynamic Graph CNN for Learning on Point Clouds [paper][summary]

    • Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, Justin M. Solomon | Arxiv 2018
  • Noise2Noise: Learning Image Restoration without Clean Data [paper] [summary]

    • Jaakko Lehtinen, Jacob Munkberg, Jon Hasselgren, Samuli Laine, Tero Karras, Miika Aittala, Timo Aila | ICML 2018
  • Hierarchical Long-term Video Prediction without Supervision [paper] [summary]

    • Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee | ICML 2018


  • Multi-Scale Dense Networks for Resource Efficient Image Classification [paper] [summary]

    • Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Q. Weinberger | ICLR 2018
  • CyCADA: Cycle-Consistent Adversarial Domain Adaptation [paper] [summary]

    • Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, K Saenko, A Efros, T Darrell | ICML 2018
  • Emergent translation in multi-agent communication [paper] [summary]

    • J. Lee, K. Cho, J. Weston and D. Kiela | ICLR 2018
  • Deep Neural Networks as Gaussian Process [Paper] [summary]

    • Jaehoon Lee, Yasaman Bahri, Roman Novak, Samuel S. Schoenholz, Jeffrey Pennington, Jascha Sohl-Dickstein | ICLR 2018
  • Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo [Paper] [TO DO]

    • MD Hoffman


  • Composing graphical models with neural networks for structured representations and fast inference [paper][summary]

    • MJ Johnson, David Duvenaud, A Wiltschko, Sandeep Datta, Ryan P. Adams
  • Low-shot visual recognition by shrinking and hallucinating features [Paper] [TO DO]

    • Bharath Hariharan and Ross Girshick | ICCV 2017


  • Structural-RNN: Deep Learning on Spatio-Temporal Graphs [paper] [summary]
    • Ashesh Jain, Amir R. Zamir, Silvio Savarese, Ashutosh Saxena | CVPR 2015
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