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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).
  
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=Paper presentation=
 
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|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]
 
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|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#Performance_Evaluation Summary]
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|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]
 
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|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]
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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] || [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]  
 
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|Mar 8 || Guillaume Verdon || 11|| || ||  
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|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]
 
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|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]
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|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 || 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]  
 
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|Mar 13 || Saifuddin Hitawala || 14 || Robust Imitation of Diverse Behaviors || [https://papers.nips.cc/paper/7116-robust-imitation-of-diverse-behaviors.pdf Paper] ||  
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|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]
 
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|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 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]
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|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]
 
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|Mar 15 || Prarthana Bhattacharyya || 17|| Wasserstein Auto-Encoders || [https://arxiv.org/pdf/1711.01558.pdf Paper]  || [Summary]  
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|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]  
 
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|Mar 15 || Changjian Li || 18|| Imagination-Augmented Agents for Deep Reinforcement Learning || [https://papers.nips.cc/paper/7152-imagination-augmented-agents-for-deep-reinforcement-learning.pdf Paper]  ||  
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|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]
 
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|Mar 20 || Travis Dunn  || 19|| Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments ||  [https://openreview.net/pdf?id=Sk2u1g-0- Paper] || [Summary]
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|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]
 
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|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]
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|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]
 
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|Mar 20 || Hamid Tahir || 21|| Wavelet Pooling for Convolution Neural Networks ||  [https://openreview.net/pdf?id=rkhlb8lCZ Paper] || Summary
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|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]
 
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|Mar 22 || Dongyang Yang|| 22|| Implicit Causal Models for Genome-wide Association Studies || [https://openreview.net/pdf?id=SyELrEeAb Paper]  ||  
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|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]
 
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|Mar 22 || Yao Li  || 23||Improving GANS Using Optimal Transport  || [https://openreview.net/pdf?id=rkQkBnJAb Paper]  ||  
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|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]
 
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|Mar 22 || Sahil Pereira || 24||End-to-End Differentiable Adversarial Imitation Learning|| [http://proceedings.mlr.press/v70/baram17a/baram17a.pdf Paper] || [http://proceedings.mlr.press/v70/baram17a/baram17a.pdf Summary]
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|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]
 
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|Mar 27 ||  Jaspreet Singh Sambee || 25|| Gated Recurrent Convolution Neural Network for OCR ||  [http://papers.nips.cc/paper/6637-gated-recurrent-convolution-neural-network-for-ocr.pdf Paper] ||  
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|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]
 
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|Mar 27 || Braden Hurl  || 26|| Spherical CNNs || [https://openreview.net/pdf?id=Hkbd5xZRb Paper]  ||  
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|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]
 
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|Mar 27 || Marko Ilievski  || 27|| Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders ||  [http://proceedings.mlr.press/v70/engel17a/engel17a.pdf Paper] ||  
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|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]
 
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|Mar 29 || Alex Pon  || 28||Wasserstein GAN || [https://arxiv.org/pdf/1701.07875.pdf Paper]  ||
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|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]
 
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|Mar 29 || Sean Walsh  || 29||Improved Training of Wasserstein GANs || [https://arxiv.org/pdf/1704.00028.pdf Paper]  ||
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|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]
 
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|Mar 29 || Jason Ku  || 30||MarrNet: 3D Shape Reconstruction via 2.5D Sketches ||[https://arxiv.org/pdf/1711.03129.pdf Paper]   ||
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|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]
 
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|Apr 3 || Tong Yang  || 31|| Dynamic Routing Between Capsules. || [http://papers.nips.cc/paper/6975-dynamic-routing-between-capsules.pdf Paper]  ||  
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|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]
 
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|Apr 3 || Benjamin Skikos || 32|| Training and Inference with Integers in Deep Neural Networks || [https://openreview.net/pdf?id=HJGXzmspb Paper]   ||  
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|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]
 
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|Apr 3 ||  Weishi Chen || 33|| Tensorized LSTMs for sequence learning || [https://arxiv.org/pdf/1711.01577.pdf Paper]  ||  
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|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] 
 
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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