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  1. "Why Should I Trust You?": Explaining the Predictions of Any Classifier
  2. 13Stat946papers
  3. ALBERT
  4. ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
  5. A Bayesian Perspective on Generalization and Stochastic Gradient Descent
  6. A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques
  7. A Game Theoretic Approach to Class-wise Selective Rationalization
  8. A Knowledge-Grounded Neural Conversation Model
  9. A Neural Representation of Sketch Drawings
  10. A universal SNP and small-indel variant caller using deep neural networks
  11. Adacompress: Adaptive compression for online computer vision services
  12. Adversarial Attacks on Copyright Detection Systems
  13. Adversarial Fisher Vectors for Unsupervised Representation Learning
  14. Annotating Object Instances with a Polygon RNN
  15. Another look at distance-weighted discrimination
  16. Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
  17. Augmix: New Data Augmentation method to increase the robustness of the algorithm
  18. Automatic Bank Fraud Detection Using Support Vector Machines
  19. BERTScore: Evaluating Text Generation with BERT
  20. Bag of Tricks for Efficient Text Classification
  21. Batch Normalization
  22. Batch Normalization Summary
  23. Bayesian Network as a Decision Tool for Predicting ALS Disease
  24. Being Bayesian about Categorical Probability
  25. Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates
  26. Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
  27. Bsodjahi
  28. CRITICAL ANALYSIS OF SELF-SUPERVISION
  29. CapsuleNets
  30. CatBoost: unbiased boosting with categorical features
  31. Co-Teaching
  32. Conditional Image Synthesis with Auxiliary Classifier GANs
  33. Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
  34. Convolutional Neural Networks for Sentence Classification
  35. Convolutional Sequence to Sequence Learning
  36. Convolutional neural network for diagnosis of viral pneumonia and COVID-19 alike diseases
  37. Countering Adversarial Images Using Input Transformations
  38. Curiosity-driven Exploration by Self-supervised Prediction
  39. DCN plus: Mixed Objective And Deep Residual Coattention for Question Answering
  40. DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS
  41. DON'T DECAY THE LEARNING RATE , INCREASE THE BATCH SIZE
  42. DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION
  43. DeepVO Towards end to end visual odometry with deep RNN
  44. Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition
  45. Deep Double Descent Where Bigger Models and More Data Hurt
  46. Deep Exploration via Bootstrapped DQN
  47. Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms
  48. Deep Learning for Extreme Multi-label Text Classification
  49. Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling
  50. Deep Residual Learning for Image Recognition
  51. Deep Residual Learning for Image Recognition Summary
  52. Deep Transfer Learning with Joint Adaptation Networks
  53. Dense Passage Retrieval for Open-Domain Question Answering
  54. Depthwise Convolution Is All You Need for Learning Multiple Visual Domains
  55. Describtion of Text Mining
  56. Dialog-based Language Learning
  57. Do Deep Neural Networks Suffer from Crowding
  58. Do Vision Transformers See Like CNN
  59. Don't Just Blame Over-parametrization
  60. Don't Just Blame Over-parametrization Summary
  61. Dynamic Routing Between Capsules
  62. Dynamic Routing Between Capsules STAT946
  63. Dynamic Routing Between Capsulesl
  64. Efficient kNN Classification with Different Numbers of Nearest Neighbors
  65. End-to-End Differentiable Adversarial Imitation Learning
  66. End to end Active Object Tracking via Reinforcement Learning
  67. Evaluating Machine Accuracy on ImageNet
  68. Extreme Multi-label Text Classification
  69. F18-STAT841-Proposal
  70. F18-STAT946-Proposal
  71. F21-STAT 441/841 CM 763-Proposal
  72. F21-STAT 940-Proposal
  73. Fairness Without Demographics in Repeated Loss Minimization
  74. FeUdal Networks for Hierarchical Reinforcement Learning
  75. Fix your classifier: the marginal value of training the last weight layer
  76. From Variational to Deterministic Autoencoders
  77. Functional regularisation for continual learning with gaussian processes
  78. Generating Image Descriptions
  79. Going Deeper with Convolutions
  80. GradientLess Descent
  81. Gradient Episodic Memory for Continual Learning
  82. Graph Structure of Neural Networks
  83. Hash Embeddings for Efficient Word Representations
  84. Hierarchical Question-Image Co-Attention for Visual Question Answering
  85. Hierarchical Representations for Efficient Architecture Search
  86. IPBoost
  87. Imagination-Augmented Agents for Deep Reinforcement Learning
  88. Imagination Augmented Agents for Deep Reinforcement Learning
  89. Improving neural networks by preventing co-adaption of feature detectors
  90. Improving neural networks by preventing co-adaption of feature detectors 2020 Fall
  91. Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
  92. Influenza Forecasting Framework based on Gaussian Processes
  93. Influenza Forecasting Framework based on Gaussian processes Summary
  94. Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
  95. Learning Combinatorial Optimzation
  96. Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
  97. Learning What and Where to Draw
  98. Learning the Number of Neurons in Deep Networks
  99. Learning to Navigate in Cities Without a Map
  100. Learning to Teach
  101. LightRNN: Memory and Computation-Efficient Recurrent Neural Networks
  102. Loss Function Search for Face Recognition
  103. MULTI-VIEW DATA GENERATION WITHOUT VIEW SUPERVISION
  104. Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
  105. MarrNet: 3D Shape Reconstruction via 2.5D Sketches
  106. Mask RCNN
  107. Memory-Based Parameter Adaptation
  108. Meta-Learning-For-Domain Generalization
  109. Meta-Learning For Domain Generalization
  110. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
  111. ModelFramework.jpg
  112. Model Agnostic Learning of Semantic Features
  113. Modular Multitask Reinforcement Learning with Policy Sketches
  114. Multi-scale Dense Networks for Resource Efficient Image Classification
  115. Music Recommender System Based using CRNN
  116. Neural Audio Synthesis of Musical Notes with WaveNet autoencoders
  117. Neural ODEs
  118. Neural Speed Reading via Skim-RNN
  119. Obfuscated Gradients Give a False Sense of Security Circumventing Defenses to Adversarial Examples
  120. On The Convergence Of ADAM And Beyond
  121. One-Shot Imitation Learning
  122. One-Shot Object Detection with Co-Attention and Co-Excitation
  123. One pixel attack for fooling deep neural networks
  124. Patch Based Convolutional Neural Network for Whole Slide Tissue Image Classification
  125. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
  126. Pixels to Graphs by Associative Embedding
  127. Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence
  128. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
  129. Poison Frogs Neural Networks
  130. Pre-Training-Tasks-For-Embedding-Based-Large-Scale-Retrieval
  131. Pre-Training Tasks For Embedding-Based Large-Scale Retrieval
  132. Predicting Floor Level For 911 Calls with Neural Network and Smartphone Sensor Data
  133. Predicting Hurricane Trajectories Using a Recurrent Neural Network
  134. Proposal for STAT946 (Deep Learning) final projects Fall 2017
  135. Reinforcement Learning of Theorem Proving
  136. Representations of Words and Phrases and their Compositionality
  137. Research Papers Classification System
  138. Research on Multiple Classification Based on Improved SVM Algorithm for Balanced Binary Decision Tree
  139. Roberta
  140. Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
  141. Robust Imitation Learning from Noisy Demonstrations
  142. Robust Imitation of Diverse Behaviors
  143. Robust Probabilistic Modeling with Bayesian Data Reweighting
  144. STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study
  145. STAT946F17/Conditional Image Generation with PixelCNN Decoders
  146. STAT946F17/Decoding with Value Networks for Neural Machine Translation
  147. STAT946F17/ Automated Curriculum Learning for Neural Networks
  148. STAT946F17/ Coupled GAN
  149. STAT946F17/ Dance Dance Convolution
  150. STAT946F17/ Improved Variational Inference with Inverse Autoregressive Flow
  151. STAT946F17/ Learning Important Features Through Propagating Activation Differences
  152. STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN
  153. STAT946F17/ Teaching Machines to Describe Images via Natural Language Feedback
  154. STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
  155. Searching For Efficient Multi Scale Architectures For Dense Image Prediction
  156. Self-Supervised Learning of Pretext-Invariant Representations
  157. Semantic Relation Classification——via Convolution Neural Network
  158. ShakeDrop Regularization
  159. Speech2Face: Learning the Face Behind a Voice
  160. Spherical CNNs
  161. Streaming Bayesian Inference for Crowdsourced Classification
  162. Summary - A Neural Representation of Sketch Drawings
  163. Summary for survey of neural networked-based cancer prediction models from microarray data
  164. Summary of A Probabilistic Approach to Neural Network Pruning
  165. SuperGLUE
  166. Superhuman AI for Multiplayer Poker
  167. Surround Vehicle Motion Prediction
  168. Synthesizing Programs for Images usingReinforced Adversarial Learning
  169. THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS
  170. Task Understanding from Confushing Multitask Data
  171. Task Understanding from Confusing Multi-task Data
  172. The Curious Case of Degeneration
  173. The Detection of Black Ice Accidents Using CNNs
  174. This Looks Like That: Deep Learning for Interpretable Image Recognition
  175. Time-series Generative Adversarial Networks
  176. Towards Deep Learning Models Resistant to Adversarial Attacks
  177. Traffic Sign Recognition System (TSRS): SVM and Convolutional Neural Network
  178. Training And Inference with Integers in Deep Neural Networks
  179. U-Time:A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging Summary
  180. Understanding Image Motion with Group Representations
  181. Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
  182. Universal Style Transfer via Feature Transforms
  183. Unsupervised Domain Adaptation with Residual Transfer Networks
  184. Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness
  185. Unsupervised Machine Translation Using Monolingual Corpora Only
  186. Unsupervised Neural Machine Translation
  187. Visual Reinforcement Learning with Imagined Goals
  188. Wasserstein Auto-Encoders
  189. Wasserstein Auto-encoders
  190. Wavelet Pooling CNN
  191. When Does Self-Supervision Improve Few-Shot Learning?
  192. When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary
  193. Wide and Deep Learning for Recommender Systems
  194. Word translation without parallel data
  195. XGBoost
  196. XGBoost: A Scalable Tree Boosting System
  197. Zero-Shot Visual Imitation
  198. a Deeper Look into Importance Sampling
  199. a Direct Formulation For Sparse PCA Using Semidefinite Programming
  200. a Dynamic Bayesian Network Click Model for Web Search Ranking
  201. a Dynamic Bayesian Network Click Model for web search ranking
  202. a New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
  203. a Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis
  204. a Rank Minimization Heuristic with Application to Minimum Order System Approximation
  205. a fair comparison of graph neural networks for graph classification
  206. a fast learning algorithm for deep belief nets
  207. a neural representation of sketch drawings
  208. acceptance-Rejection Sampling
  209. adaptive dimension reduction for clustering high dimensional data
  210. again on Markov Chain
  211. an HDP-HMM for Systems with State Persistence
  212. bayesian and Frequentist Schools of Thought
  213. binomial Probability Monte Carlo Sampling June 2 2009
  214. cardinality Restricted Boltzmann Machines
  215. compressed Sensing Reconstruction via Belief Propagation
  216. compressive Sensing
  217. compressive Sensing (Candes)
  218. conditional neural process
  219. consistency of Trace Norm Minimization
  220. context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
  221. continuous space language models
  222. contributions on Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
  223. contributions on Quantifying Cancer Progression with Conjunctive Bayesian Networks
  224. contributions on Video-Based Face Recognition Using Adaptive Hidden Markov Models
  225. convex and Semi Nonnegative Matrix Factorization
  226. copyofstat341
  227. decentralised Data Fusion: A Graphical Model Approach (Summary)
  228. deepGenerativeModels
  229. deep Convolutional Neural Networks For LVCSR
  230. deep Generative Stochastic Networks Trainable by Backprop
  231. deep Learning of the tissue-regulated splicing code
  232. deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
  233. deep Sparse Rectifier Neural Networks
  234. deep neural networks for acoustic modeling in speech recognition
  235. deflation Method for Penalized Matrix Decomposition Sparse PCA
  236. deflation Methods for Sparse PCA
  237. dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
  238. discLDA: Discriminative Learning for Dimensionality Reduction and Classification
  239. distributed Representations of Words and Phrases and their Compositionality
  240. dropout
  241. extracting and Composing Robust Features with Denoising Autoencoders
  242. f10 Stat841 digest
  243. f11Stat841EditorSignUp
  244. f11Stat841presentation
  245. f11Stat841proposal
  246. f11Stat946ass
  247. f11Stat946papers
  248. f11Stat946presentation
  249. f11stat946EditorSignUp
  250. f14Stat842EditorSignUp

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