# Difference between revisions of "stat946w18"

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|Mar 6 || Raphael Tang || 8|| Snapshot Ensembles: Train 1, Get M for Free || [https://arxiv.org/abs/1704.00109 Paper] || | |Mar 6 || Raphael Tang || 8|| Snapshot Ensembles: Train 1, Get M for Free || [https://arxiv.org/abs/1704.00109 Paper] || | ||

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− | |Mar 6 ||Fan Xia || 9|| Breaking the Softmax Bottleneck: A High-Rank RNN Language Model ||[https://openreview.net/pdf?id=HkwZSG-CZ Paper] || | + | |Mar 6 ||Fan Xia || 9|| Breaking the Softmax Bottleneck: A High-Rank RNN Language Model ||[https://openreview.net/pdf?id=HkwZSG-CZ Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Breaking the Softmax Bottleneck: A High-Rank RNN Language Model Summary] |

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|Mar 8 || Alex (Xian) Wang || 10 || Self-Normalizing Neural Networks || [http://papers.nips.cc/paper/6698-self-normalizing-neural-networks.pdf Paper] || | |Mar 8 || Alex (Xian) Wang || 10 || Self-Normalizing Neural Networks || [http://papers.nips.cc/paper/6698-self-normalizing-neural-networks.pdf Paper] || |

## Revision as of 22:20, 23 February 2018

# List of Papers

# Record your contributions here [1]

Use the following notations:

P: You have written a summary/critique on the paper.

T: You had a technical contribution on a paper (excluding the paper that you present).

E: You had an editorial contribution on a paper (excluding the paper that you present).

Your feedback on presentations

# Paper presentation

Date | Name | Paper number | Title | Link to the paper | Link to the summary |

Feb 15 (example) | Ri Wang | Sequence to sequence learning with neural networks. | Paper | Summary | |

Feb 27 | 1 | ||||

Feb 27 | 2 | ||||

Feb 27 | 3 | ||||

Mar 1 | Peter Forsyth | 4 | Unsupervised Machine Translation Using Monolingual Corpora Only | Paper | [Summary] |

Mar 1 | wenqing liu | 5 | Spectral Normalization for Generative Adversarial Networks | Paper | Summary |

Mar 1 | Ilia Sucholutsky | 6 | One-Shot Imitation Learning | Paper | Summary |

Mar 6 | George (Shiyang) Wen | 7 | AmbientGAN: Generative models from lossy measurements | Paper | |

Mar 6 | Raphael Tang | 8 | Snapshot Ensembles: Train 1, Get M for Free | Paper | |

Mar 6 | Fan Xia | 9 | Breaking the Softmax Bottleneck: A High-Rank RNN Language Model | Paper | the Softmax Bottleneck: A High-Rank RNN Language Model Summary |

Mar 8 | Alex (Xian) Wang | 10 | Self-Normalizing Neural Networks | Paper | |

Mar 8 | Guillaume Verdon | 11 | |||

Mar 8 | Wei Tao Chen | 12 | Learning Sparse Neural Networks through L_0 Regularization | [2] | |

Mar 13 | Chunshang Li | 13 | UNDERSTANDING IMAGE MOTION WITH GROUP REPRESENTATIONS | Paper | |

Mar 13 | Saifuddin Hitawala | 14 | Thinking Fast and Slow with Deep Learning and Tree Search | Paper | |

Mar 13 | Taylor Denouden | 15 | A neural representation of sketch drawings | Paper | [Summary] |

Mar 15 | Zehao xu | 16 | Synthetic and natural noise both break neural machine translation | ||

Mar 15 | Prarthana Bhattacharyya | 17 | Semi-Supervised Learning for Optical Flow with Generative Adversarial Networks | [3] | [Summary] |

Mar 15 | Changjian Li | 18 | Imagination-Augmented Agents for Deep Reinforcement Learning | Paper | |

Mar 20 | Travis Dunn | 19 | Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments | Paper | [Summary] |

Mar 20 | Sushrut Bhalla | 20 | MaskRNN: Instance Level Video Object Segmentation | Paper | [Summary] |

Mar 20 | Hamid Tahir | 21 | Wavelet Pooling for Convolution Neural Networks | Paper | Summary |

Mar 22 | Dongyang Yang | 22 | Don't Decay the Learning Rate, Increase the Batch Size | Paper | |

Mar 22 | Yao Li | 23 | Toward Multimodal Image-to-Image Translation | Paper | |

Mar 22 | Sahil Pereira | 24 | End-to-End Differentiable Adversarial Imitation Learning | Paper | Summary |

Mar 27 | Jaspreet Singh Sambee | 25 | Gated Recurrent Convolution Neural Network for OCR | Paper | |

Mar 27 | Braden Hurl | 26 | Spherical CNNs | Paper | |

Mar 27 | Marko Ilievski | 27 | Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders | Paper | |

Mar 29 | Alex Pon | 28 | Wasserstein GAN | Paper | |

Mar 29 | Sean Walsh | 29 | Improved Training of Wasserstein GANs | Paper | |

Mar 29 | Jason Ku | 30 | MarrNet: 3D Shape Reconstruction via 2.5D Sketches | Paper | |

Apr 3 | Tong Yang | 31 | Dynamic Routing Between Capsules. | Paper | |

Apr 3 | Benjamin Skikos | 32 | Training and Inference with Integers in Deep Neural Networks | Paper | |

Apr 3 | Weishi Chen | 33 |