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  1. STAT946F17/ Learning Important Features Through Propagating Activation Differences
  2. STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN
  3. STAT946F17/ Teaching Machines to Describe Images via Natural Language Feedback
  4. STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
  5. Searching For Efficient Multi Scale Architectures For Dense Image Prediction
  6. Self-Supervised Learning of Pretext-Invariant Representations
  7. Semantic Relation Classification——via Convolution Neural Network
  8. ShakeDrop Regularization
  9. Speech2Face: Learning the Face Behind a Voice
  10. Spherical CNNs
  11. Streaming Bayesian Inference for Crowdsourced Classification
  12. Summary - A Neural Representation of Sketch Drawings
  13. Summary for survey of neural networked-based cancer prediction models from microarray data
  14. Summary of A Probabilistic Approach to Neural Network Pruning
  15. SuperGLUE
  16. Superhuman AI for Multiplayer Poker
  17. Surround Vehicle Motion Prediction
  18. Synthesizing Programs for Images usingReinforced Adversarial Learning
  19. THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS
  20. Task Understanding from Confushing Multitask Data
  21. Task Understanding from Confusing Multi-task Data
  22. The Curious Case of Degeneration
  23. The Detection of Black Ice Accidents Using CNNs
  24. This Looks Like That: Deep Learning for Interpretable Image Recognition
  25. Time-series Generative Adversarial Networks
  26. Towards Deep Learning Models Resistant to Adversarial Attacks
  27. Traffic Sign Recognition System (TSRS): SVM and Convolutional Neural Network
  28. Training And Inference with Integers in Deep Neural Networks
  29. U-Time:A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging Summary
  30. Understanding Image Motion with Group Representations
  31. Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
  32. Universal Style Transfer via Feature Transforms
  33. Unsupervised Domain Adaptation with Residual Transfer Networks
  34. Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness
  35. Unsupervised Machine Translation Using Monolingual Corpora Only
  36. Unsupervised Neural Machine Translation
  37. Visual Reinforcement Learning with Imagined Goals
  38. Wasserstein Auto-Encoders
  39. Wasserstein Auto-encoders
  40. Wavelet Pooling CNN
  41. When Does Self-Supervision Improve Few-Shot Learning?
  42. When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary
  43. Wide and Deep Learning for Recommender Systems
  44. Word translation without parallel data
  45. XGBoost
  46. XGBoost: A Scalable Tree Boosting System
  47. Zero-Shot Visual Imitation
  48. a Deeper Look into Importance Sampling
  49. a Direct Formulation For Sparse PCA Using Semidefinite Programming
  50. a Dynamic Bayesian Network Click Model for Web Search Ranking
  51. a Dynamic Bayesian Network Click Model for web search ranking
  52. a New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
  53. a Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis
  54. a Rank Minimization Heuristic with Application to Minimum Order System Approximation
  55. a fair comparison of graph neural networks for graph classification
  56. a fast learning algorithm for deep belief nets
  57. a neural representation of sketch drawings
  58. acceptance-Rejection Sampling
  59. adaptive dimension reduction for clustering high dimensional data
  60. again on Markov Chain
  61. an HDP-HMM for Systems with State Persistence
  62. bayesian and Frequentist Schools of Thought
  63. binomial Probability Monte Carlo Sampling June 2 2009
  64. cardinality Restricted Boltzmann Machines
  65. compressed Sensing Reconstruction via Belief Propagation
  66. compressive Sensing
  67. compressive Sensing (Candes)
  68. conditional neural process
  69. consistency of Trace Norm Minimization
  70. context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
  71. continuous space language models
  72. contributions on Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
  73. contributions on Quantifying Cancer Progression with Conjunctive Bayesian Networks
  74. contributions on Video-Based Face Recognition Using Adaptive Hidden Markov Models
  75. convex and Semi Nonnegative Matrix Factorization
  76. copyofstat341
  77. decentralised Data Fusion: A Graphical Model Approach (Summary)
  78. deepGenerativeModels
  79. deep Convolutional Neural Networks For LVCSR
  80. deep Generative Stochastic Networks Trainable by Backprop
  81. deep Learning of the tissue-regulated splicing code
  82. deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
  83. deep Sparse Rectifier Neural Networks
  84. deep neural networks for acoustic modeling in speech recognition
  85. deflation Method for Penalized Matrix Decomposition Sparse PCA
  86. deflation Methods for Sparse PCA
  87. dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
  88. discLDA: Discriminative Learning for Dimensionality Reduction and Classification
  89. distributed Representations of Words and Phrases and their Compositionality
  90. dropout
  91. extracting and Composing Robust Features with Denoising Autoencoders
  92. f10 Stat841 digest
  93. f11Stat841EditorSignUp
  94. f11Stat841presentation
  95. f11Stat841proposal
  96. f11Stat946ass
  97. f11Stat946papers
  98. f11Stat946presentation
  99. f11stat946EditorSignUp
  100. f14Stat842EditorSignUp

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