# Difference between revisions of "stat946w18"

From statwiki

m (Changed protection level for "stat946w18" ([Edit=Allow only administrators] (indefinite) [Move=Allow only administrators] (indefinite)) [cascading]) |
|||

(49 intermediate revisions by 22 users not shown) | |||

Line 11: | Line 11: | ||

E: You had an editorial 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). | ||

− | [https://docs.google.com/forms/d/ | + | |

+ | |||

+ | [https://docs.google.com/forms/d/e/1FAIpQLSdcfYZu5cvpsbzf0Nlxh9TFk8k1m5vUgU1vCLHQNmJog4xSHw/viewform?usp=sf_link Your feedback on presentations] | ||

=Paper presentation= | =Paper presentation= | ||

Line 37: | Line 39: | ||

|Mar 1 || wenqing liu || 5|| Spectral Normalization for Generative Adversarial Networks || [https://openreview.net/pdf?id=B1QRgziT- Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/Spectral_normalization_for_generative_adversial_network Summary] | |Mar 1 || wenqing liu || 5|| Spectral Normalization for Generative Adversarial Networks || [https://openreview.net/pdf?id=B1QRgziT- Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/Spectral_normalization_for_generative_adversial_network Summary] | ||

|- | |- | ||

− | |Mar 1 || Ilia Sucholutsky || 6|| One-Shot Imitation Learning || [https://papers.nips.cc/paper/6709-one-shot-imitation-learning.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=One-Shot_Imitation_Learning | + | |Mar 1 || Ilia Sucholutsky || 6|| One-Shot Imitation Learning || [https://papers.nips.cc/paper/6709-one-shot-imitation-learning.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=One-Shot_Imitation_Learning Summary] |

|- | |- | ||

|Mar 6 || George (Shiyang) Wen || 7|| AmbientGAN: Generative models from lossy measurements || [https://openreview.net/pdf?id=Hy7fDog0b Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/AmbientGAN:_Generative_Models_from_Lossy_Measurements Summary] | |Mar 6 || George (Shiyang) Wen || 7|| AmbientGAN: Generative models from lossy measurements || [https://openreview.net/pdf?id=Hy7fDog0b Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/AmbientGAN:_Generative_Models_from_Lossy_Measurements Summary] | ||

Line 47: | Line 49: | ||

|Mar 8 || Alex (Xian) Wang || 10 || Self-Normalizing Neural Networks || [http://papers.nips.cc/paper/6698-self-normalizing-neural-networks.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/Self_Normalizing_Neural_Networks Summary] | |Mar 8 || Alex (Xian) Wang || 10 || Self-Normalizing Neural Networks || [http://papers.nips.cc/paper/6698-self-normalizing-neural-networks.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/Self_Normalizing_Neural_Networks Summary] | ||

|- | |- | ||

− | |Mar 8 || | + | |Mar 8 || Michael Broughton || 11|| Convergence of Adam and beyond || [https://openreview.net/pdf?id=ryQu7f-RZ Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=On_The_Convergence_Of_ADAM_And_Beyond Summary] |

|- | |- | ||

|Mar 8 || Wei Tao Chen || 12|| Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data || [https://openreview.net/forum?id=ryBnUWb0b Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/Predicting_Floor-Level_for_911_Calls_with_Neural_Networks_and_Smartphone_Sensor_Data Summary] | |Mar 8 || Wei Tao Chen || 12|| Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data || [https://openreview.net/forum?id=ryBnUWb0b Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/Predicting_Floor-Level_for_911_Calls_with_Neural_Networks_and_Smartphone_Sensor_Data Summary] | ||

|- | |- | ||

− | |Mar 13 || Chunshang Li || 13 || UNDERSTANDING IMAGE MOTION WITH GROUP REPRESENTATIONS || [https://openreview.net/pdf?id=SJLlmG-AZ Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Understanding_Image_Motion_with_Group_Representations] | + | |Mar 13 || Chunshang Li || 13 || UNDERSTANDING IMAGE MOTION WITH GROUP REPRESENTATIONS || [https://openreview.net/pdf?id=SJLlmG-AZ Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Understanding_Image_Motion_with_Group_Representations Summary] |

|- | |- | ||

− | |Mar 13 || Saifuddin Hitawala || 14 || | + | |Mar 13 || Saifuddin Hitawala || 14 || Robust Imitation of Diverse Behaviors || [https://papers.nips.cc/paper/7116-robust-imitation-of-diverse-behaviors.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Robust_Imitation_of_Diverse_Behaviors Summary] |

|- | |- | ||

− | |Mar 13 || Taylor Denouden || 15|| A neural representation of sketch drawings || [https://arxiv.org/pdf/1704.03477.pdf Paper] || [Summary] | + | |Mar 13 || Taylor Denouden || 15|| A neural representation of sketch drawings || [https://arxiv.org/pdf/1704.03477.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=A_Neural_Representation_of_Sketch_Drawings Summary] |

|- | |- | ||

|Mar 15 || Zehao Xu || 16|| Synthetic and natural noise both break neural machine translation || [https://openreview.net/pdf?id=BJ8vJebC- Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/Synthetic_and_natural_noise_both_break_neural_machine_translation Summary] | |Mar 15 || Zehao Xu || 16|| Synthetic and natural noise both break neural machine translation || [https://openreview.net/pdf?id=BJ8vJebC- Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/Synthetic_and_natural_noise_both_break_neural_machine_translation Summary] | ||

|- | |- | ||

− | |Mar 15 || Prarthana Bhattacharyya || 17|| | + | |Mar 15 || Prarthana Bhattacharyya || 17|| Wasserstein Auto-Encoders || [https://arxiv.org/pdf/1711.01558.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Wasserstein_Auto-Encoders Summary] |

|- | |- | ||

− | |Mar 15 || Changjian Li || 18|| | + | |Mar 15 || Changjian Li || 18|| Label-Free Supervision of Neural Networks with Physics and Domain Knowledge || [https://arxiv.org/pdf/1609.05566.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Label-Free_Supervision_of_Neural_Networks_with_Physics_and_Domain_Knowledge Summary] |

|- | |- | ||

− | |Mar 20 || Travis Dunn || 19|| Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments || [https://openreview.net/pdf?id=Sk2u1g-0- Paper] || [Summary] | + | |Mar 20 || Travis Dunn || 19|| Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments || [https://openreview.net/pdf?id=Sk2u1g-0- Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Continuous_Adaptation_via_Meta-Learning_in_Nonstationary_and_Competitive_Environments Summary] |

|- | |- | ||

− | |Mar 20 || Sushrut Bhalla || 20|| MaskRNN: Instance Level Video Object Segmentation || [https://papers.nips.cc/paper/6636-maskrnn-instance-level-video-object-segmentation.pdf Paper] || [Summary] | + | |Mar 20 || Sushrut Bhalla || 20|| MaskRNN: Instance Level Video Object Segmentation || [https://papers.nips.cc/paper/6636-maskrnn-instance-level-video-object-segmentation.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/MaskRNN:_Instance_Level_Video_Object_Segmentation Summary] |

|- | |- | ||

− | |Mar 20 || Hamid Tahir || 21|| Wavelet Pooling for Convolution Neural Networks || [https://openreview.net/pdf?id=rkhlb8lCZ Paper] || Summary | + | |Mar 20 || Hamid Tahir || 21|| Wavelet Pooling for Convolution Neural Networks || [https://openreview.net/pdf?id=rkhlb8lCZ Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Wavelet_Pooling_CNN Summary] |

|- | |- | ||

− | |Mar 22 || Dongyang Yang|| 22|| Implicit Causal Models for Genome-wide Association Studies || [https://openreview.net/pdf?id=SyELrEeAb Paper] || | + | |Mar 22 || Dongyang Yang|| 22|| Implicit Causal Models for Genome-wide Association Studies || [https://openreview.net/pdf?id=SyELrEeAb Paper] ||[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/Implicit_Causal_Models_for_Genome-wide_Association_Studies Summary] |

|- | |- | ||

− | |Mar 22 || Yao Li || 23|| | + | |Mar 22 || Yao Li || 23||Improving GANs Using Optimal Transport || [https://openreview.net/pdf?id=rkQkBnJAb Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/IMPROVING_GANS_USING_OPTIMAL_TRANSPORT Summary] |

|- | |- | ||

− | |Mar 22 || Sahil Pereira || 24||End-to-End Differentiable Adversarial Imitation Learning|| [http://proceedings.mlr.press/v70/baram17a/baram17a.pdf Paper] || [ | + | |Mar 22 || Sahil Pereira || 24||End-to-End Differentiable Adversarial Imitation Learning|| [http://proceedings.mlr.press/v70/baram17a/baram17a.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=End-to-End_Differentiable_Adversarial_Imitation_Learning Summary] |

|- | |- | ||

− | |Mar 27 || Jaspreet Singh Sambee || 25|| | + | |Mar 27 || Jaspreet Singh Sambee || 25|| Do Deep Neural Networks Suffer from Crowding? || [http://papers.nips.cc/paper/7146-do-deep-neural-networks-suffer-from-crowding.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Do_Deep_Neural_Networks_Suffer_from_Crowding Summary] |

|- | |- | ||

− | |Mar 27 || Braden Hurl || 26|| Spherical CNNs || [https://openreview.net/pdf?id=Hkbd5xZRb Paper] || | + | |Mar 27 || Braden Hurl || 26|| Spherical CNNs || [https://openreview.net/pdf?id=Hkbd5xZRb Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Spherical_CNNs Summary] |

|- | |- | ||

− | |Mar 27 || Marko Ilievski || 27|| Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders || [http://proceedings.mlr.press/v70/engel17a/engel17a.pdf Paper] || | + | |Mar 27 || Marko Ilievski || 27|| Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders || [http://proceedings.mlr.press/v70/engel17a/engel17a.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Neural_Audio_Synthesis_of_Musical_Notes_with_WaveNet_autoencoders Summary] |

|- | |- | ||

− | |Mar 29 || Alex Pon || 28|| | + | |Mar 29 || Alex Pon || 28||PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space || [https://arxiv.org/abs/1706.02413 Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=PointNet%2B%2B:_Deep_Hierarchical_Feature_Learning_on_Point_Sets_in_a_Metric_Space Summary] |

|- | |- | ||

− | |Mar 29 || Sean Walsh || 29|| | + | |Mar 29 || Sean Walsh || 29||Multi-scale Dense Networks for Resource Efficient Image Classification || [https://arxiv.org/pdf/1703.09844.pdf Paper] ||[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Multi-scale_Dense_Networks_for_Resource_Efficient_Image_Classification#Architecture Summary] |

|- | |- | ||

− | |Mar 29 || Jason Ku || 30||MarrNet: 3D Shape Reconstruction via 2.5D Sketches | + | |Mar 29 || Jason Ku || 30||MarrNet: 3D Shape Reconstruction via 2.5D Sketches || [https://arxiv.org/pdf/1711.03129.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=MarrNet:_3D_Shape_Reconstruction_via_2.5D_Sketches Summary] |

|- | |- | ||

− | |Apr 3 || Tong Yang || 31|| Dynamic Routing Between Capsules. || [http://papers.nips.cc/paper/6975-dynamic-routing-between-capsules.pdf Paper] || | + | |Apr 3 || Tong Yang || 31|| Dynamic Routing Between Capsules. || [http://papers.nips.cc/paper/6975-dynamic-routing-between-capsules.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Dynamic_Routing_Between_Capsules_STAT946 Summary] |

|- | |- | ||

− | |Apr 3 || Benjamin Skikos || 32|| Training and Inference with Integers in Deep Neural Networks || [https://openreview.net/pdf?id=HJGXzmspb Paper] | + | |Apr 3 || Benjamin Skikos || 32|| Training and Inference with Integers in Deep Neural Networks || [https://openreview.net/pdf?id=HJGXzmspb Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Training_And_Inference_with_Integers_in_Deep_Neural_Networks Summary] |

|- | |- | ||

− | |Apr 3 || Weishi Chen || 33|| Tensorized LSTMs for | + | |Apr 3 || Weishi Chen || 33|| Tensorized LSTMs for Sequence Learning || [https://arxiv.org/pdf/1711.01577.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat946w18/Tensorized_LSTMs&action=edit&redlink=1 Summary] |

|- | |- |

## Latest revision as of 18:05, 19 November 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 | Summary |

Mar 6 | Raphael Tang | 8 | Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolutional Layers | Paper | Summary |

Mar 6 | Fan Xia | 9 | Word translation without parallel data | Paper | Summary |

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

Mar 8 | Michael Broughton | 11 | Convergence of Adam and beyond | Paper | Summary |

Mar 8 | Wei Tao Chen | 12 | Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data | Paper | Summary |

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

Mar 13 | Saifuddin Hitawala | 14 | Robust Imitation of Diverse Behaviors | Paper | Summary |

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 | Paper | Summary |

Mar 15 | Prarthana Bhattacharyya | 17 | Wasserstein Auto-Encoders | Paper | Summary |

Mar 15 | Changjian Li | 18 | Label-Free Supervision of Neural Networks with Physics and Domain Knowledge | Paper | Summary |

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 | Implicit Causal Models for Genome-wide Association Studies | Paper | Summary |

Mar 22 | Yao Li | 23 | Improving GANs Using Optimal Transport | Paper | Summary |

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

Mar 27 | Jaspreet Singh Sambee | 25 | Do Deep Neural Networks Suffer from Crowding? | Paper | Summary |

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

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

Mar 29 | Alex Pon | 28 | PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space | Paper | Summary |

Mar 29 | Sean Walsh | 29 | Multi-scale Dense Networks for Resource Efficient Image Classification | Paper | Summary |

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

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

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

Apr 3 | Weishi Chen | 33 | Tensorized LSTMs for Sequence Learning | Paper | Summary |