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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 Knowledge-Grounded Neural Conversation Model
  8. A Neural Representation of Sketch Drawings
  9. A universal SNP and small-indel variant caller using deep neural networks
  10. Adacompress: Adaptive compression for online computer vision services
  11. Adversarial Attacks on Copyright Detection Systems
  12. Adversarial Fisher Vectors for Unsupervised Representation Learning
  13. Annotating Object Instances with a Polygon RNN
  14. Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
  15. Augmix: New Data Augmentation method to increase the robustness of the algorithm
  16. BERTScore: Evaluating Text Generation with BERT
  17. Bag of Tricks for Efficient Text Classification
  18. Batch Normalization
  19. Batch Normalization Summary
  20. Being Bayesian about Categorical Probability
  21. Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates
  22. CRITICAL ANALYSIS OF SELF-SUPERVISION
  23. CapsuleNets
  24. Co-Teaching
  25. Conditional Image Synthesis with Auxiliary Classifier GANs
  26. Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
  27. Convolutional Neural Networks for Sentence Classification
  28. Convolutional Sequence to Sequence Learning
  29. Countering Adversarial Images Using Input Transformations
  30. Curiosity-driven Exploration by Self-supervised Prediction
  31. DCN plus: Mixed Objective And Deep Residual Coattention for Question Answering
  32. DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS
  33. DON'T DECAY THE LEARNING RATE , INCREASE THE BATCH SIZE
  34. DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION
  35. DeepVO Towards end to end visual odometry with deep RNN
  36. Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition
  37. Deep Exploration via Bootstrapped DQN
  38. Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms
  39. Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling
  40. Deep Residual Learning for Image Recognition
  41. Deep Transfer Learning with Joint Adaptation Networks
  42. Dense Passage Retrieval for Open-Domain Question Answering
  43. Describtion of Text Mining
  44. Dialog-based Language Learning
  45. Do Deep Neural Networks Suffer from Crowding
  46. Dynamic Routing Between Capsules
  47. Dynamic Routing Between Capsules STAT946
  48. Dynamic Routing Between Capsulesl
  49. Efficient kNN Classification with Different Numbers of Nearest Neighbors
  50. End-to-End Differentiable Adversarial Imitation Learning
  51. End to end Active Object Tracking via Reinforcement Learning
  52. Evaluating Machine Accuracy on ImageNet
  53. Extreme Multi-label Text Classification
  54. F18-STAT841-Proposal
  55. F18-STAT946-Proposal
  56. F20-STAT 441/841 CM 763-Proposal
  57. F20-STAT 946-Proposal
  58. Fairness Without Demographics in Repeated Loss Minimization
  59. FeUdal Networks for Hierarchical Reinforcement Learning
  60. Fix your classifier: the marginal value of training the last weight layer
  61. From Variational to Deterministic Autoencoders
  62. Functional regularisation for continual learning with gaussian processes
  63. Generating Image Descriptions
  64. Going Deeper with Convolutions
  65. GradientLess Descent
  66. Gradient Episodic Memory for Continual Learning
  67. Graph Structure of Neural Networks
  68. Hash Embeddings for Efficient Word Representations
  69. Hierarchical Question-Image Co-Attention for Visual Question Answering
  70. Hierarchical Representations for Efficient Architecture Search
  71. IPBoost
  72. Imagination-Augmented Agents for Deep Reinforcement Learning
  73. Imagination Augmented Agents for Deep Reinforcement Learning
  74. Improving neural networks by preventing co-adaption of feature detectors
  75. Improving neural networks by preventing co-adaption of feature detectors 2020 Fall
  76. Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
  77. Influenza Forecasting Framework based on Gaussian Processes
  78. Influenza Forecasting Framework based on Gaussian processes Summary
  79. Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
  80. Learning Combinatorial Optimzation
  81. Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
  82. Learning What and Where to Draw
  83. Learning the Number of Neurons in Deep Networks
  84. Learning to Navigate in Cities Without a Map
  85. Learning to Teach
  86. LightRNN: Memory and Computation-Efficient Recurrent Neural Networks
  87. Loss Function Search for Face Recognition
  88. MULTI-VIEW DATA GENERATION WITHOUT VIEW SUPERVISION
  89. Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
  90. MarrNet: 3D Shape Reconstruction via 2.5D Sketches
  91. Mask RCNN
  92. Memory-Based Parameter Adaptation
  93. Meta-Learning-For-Domain Generalization
  94. Meta-Learning For Domain Generalization
  95. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
  96. ModelFramework.jpg
  97. Model Agnostic Learning of Semantic Features
  98. Modular Multitask Reinforcement Learning with Policy Sketches
  99. Multi-scale Dense Networks for Resource Efficient Image Classification
  100. Music Recommender System Based using CRNN
  101. Neural Audio Synthesis of Musical Notes with WaveNet autoencoders
  102. Neural ODEs
  103. Neural Speed Reading via Skim-RNN
  104. Obfuscated Gradients Give a False Sense of Security Circumventing Defenses to Adversarial Examples
  105. On The Convergence Of ADAM And Beyond
  106. One-Shot Imitation Learning
  107. One-Shot Object Detection with Co-Attention and Co-Excitation
  108. One pixel attack for fooling deep neural networks
  109. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
  110. Pixels to Graphs by Associative Embedding
  111. Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence
  112. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
  113. Pre-Training-Tasks-For-Embedding-Based-Large-Scale-Retrieval
  114. Pre-Training Tasks For Embedding-Based Large-Scale Retrieval
  115. Predicting Floor Level For 911 Calls with Neural Network and Smartphone Sensor Data
  116. Proposal for STAT946 (Deep Learning) final projects Fall 2017
  117. Reinforcement Learning of Theorem Proving
  118. Representations of Words and Phrases and their Compositionality
  119. Research Papers Classification System
  120. Roberta
  121. Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
  122. Robust Imitation of Diverse Behaviors
  123. Robust Probabilistic Modeling with Bayesian Data Reweighting
  124. STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study
  125. STAT946F17/Conditional Image Generation with PixelCNN Decoders
  126. STAT946F17/Decoding with Value Networks for Neural Machine Translation
  127. STAT946F17/ Automated Curriculum Learning for Neural Networks
  128. STAT946F17/ Coupled GAN
  129. STAT946F17/ Dance Dance Convolution
  130. STAT946F17/ Improved Variational Inference with Inverse Autoregressive Flow
  131. STAT946F17/ Learning Important Features Through Propagating Activation Differences
  132. STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN
  133. STAT946F17/ Teaching Machines to Describe Images via Natural Language Feedback
  134. STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
  135. Searching For Efficient Multi Scale Architectures For Dense Image Prediction
  136. Self-Supervised Learning of Pretext-Invariant Representations
  137. Semantic Relation Classification——via Convolution Neural Network
  138. ShakeDrop Regularization
  139. Speech2Face: Learning the Face Behind a Voice
  140. Spherical CNNs
  141. Streaming Bayesian Inference for Crowdsourced Classification
  142. Summary - A Neural Representation of Sketch Drawings
  143. Summary for survey of neural networked-based cancer prediction models from microarray data
  144. SuperGLUE
  145. Superhuman AI for Multiplayer Poker
  146. Surround Vehicle Motion Prediction
  147. Synthesizing Programs for Images usingReinforced Adversarial Learning
  148. THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS
  149. Task Understanding from Confushing Multitask Data
  150. Task Understanding from Confusing Multi-task Data
  151. The Curious Case of Degeneration
  152. This Looks Like That: Deep Learning for Interpretable Image Recognition
  153. Time-series Generative Adversarial Networks
  154. Towards Deep Learning Models Resistant to Adversarial Attacks
  155. Training And Inference with Integers in Deep Neural Networks
  156. Understanding Image Motion with Group Representations
  157. Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
  158. Universal Style Transfer via Feature Transforms
  159. Unsupervised Domain Adaptation with Residual Transfer Networks
  160. Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness
  161. Unsupervised Machine Translation Using Monolingual Corpora Only
  162. Unsupervised Neural Machine Translation
  163. Visual Reinforcement Learning with Imagined Goals
  164. Wasserstein Auto-Encoders
  165. Wasserstein Auto-encoders
  166. Wavelet Pooling CNN
  167. When Does Self-Supervision Improve Few-Shot Learning?
  168. When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary
  169. Word translation without parallel data
  170. XGBoost: A Scalable Tree Boosting System
  171. Zero-Shot Visual Imitation
  172. a Deeper Look into Importance Sampling
  173. a Direct Formulation For Sparse PCA Using Semidefinite Programming
  174. a Dynamic Bayesian Network Click Model for web search ranking
  175. a Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis
  176. a Rank Minimization Heuristic with Application to Minimum Order System Approximation
  177. a fair comparison of graph neural networks for graph classification
  178. a fast learning algorithm for deep belief nets
  179. a neural representation of sketch drawings
  180. adaptive dimension reduction for clustering high dimensional data
  181. again on Markov Chain
  182. bayesian and Frequentist Schools of Thought
  183. binomial Probability Monte Carlo Sampling June 2 2009
  184. compressive Sensing
  185. conditional neural process
  186. consistency of Trace Norm Minimization
  187. context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
  188. contributions on Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
  189. contributions on Quantifying Cancer Progression with Conjunctive Bayesian Networks
  190. contributions on Video-Based Face Recognition Using Adaptive Hidden Markov Models
  191. copyofstat341
  192. decentralised Data Fusion: A Graphical Model Approach (Summary)
  193. deepGenerativeModels
  194. deep Convolutional Neural Networks For LVCSR
  195. deep Learning of the tissue-regulated splicing code
  196. deep neural networks for acoustic modeling in speech recognition
  197. deflation Method for Penalized Matrix Decomposition Sparse PCA
  198. deflation Methods for Sparse PCA
  199. dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
  200. discLDA: Discriminative Learning for Dimensionality Reduction and Classification
  201. distributed Representations of Words and Phrases and their Compositionality
  202. f11Stat841EditorSignUp
  203. f11Stat841presentation
  204. f11Stat841proposal
  205. f11Stat946papers
  206. f11Stat946presentation
  207. f11stat946EditorSignUp
  208. f14Stat842EditorSignUp
  209. f15Stat946PaperSignUp
  210. f17Stat946PaperSignUp
  211. generating Random Numbers
  212. genetics
  213. hamming Distance Metric Learning
  214. hierarchical Dirichlet Processes
  215. importance Sampling June 2 2009
  216. importance Sampling and Markov Chain Monte Carlo (MCMC)
  217. importance Sampling and Monte Carlo Simulation
  218. incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary)
  219. independent Component Analysis: algorithms and applications
  220. is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction
  221. kernel Dimension Reduction in Regression
  222. kernel Spectral Clustering for Community Detection in Complex Networks
  223. kernelized Locality-Sensitive Hashing
  224. kernelized Sorting
  225. learn what not to learn
  226. learning2reasoning
  227. learning Convolutional Feature Hierarchies for Visual Recognition
  228. learning Fast Approximations of Sparse Coding
  229. learning Spectral Clustering, With Application To Speech Separation
  230. learning a Nonlinear Embedding by Preserving Class Neighborhood Structure
  231. link to my paper
  232. mULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION
  233. main Page
  234. mark Your Contribution here
  235. mark your contribution here
  236. markov Chain Definitions
  237. matrix Completion with Noise
  238. maximum-Margin Matrix Factorization
  239. maximum Variance Unfolding (June 2 2009)
  240. maximum likelihood estimation of intrinsic dimension
  241. meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
  242. measuring Statistical Dependence with Hilbert-Schmidt Norm
  243. measuring and testing dependence by correlation of distances
  244. monte Carlo Integration
  245. monte Carlo methods
  246. neighbourhood Components Analysis
  247. neural Machine Translation: Jointly Learning to Align and Translate
  248. nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization
  249. nonparametric Latent Feature Models for Link Prediction
  250. on using very large target vocabulary for neural machine translation
  251. orthogonal gradient descent for continual learning
  252. overfeat: integrated recognition, localization and detection using convolutional networks
  253. paper 13
  254. paper Summaries
  255. policy optimization with demonstrations
  256. proof
  257. proof of Lemma 1
  258. proof of Theorem 1
  259. proposal Fall 2010
  260. proposal for STAT946 (Deep Learning) final projects Fall 2015
  261. proposal for STAT946 projects
  262. proposal for STAT946 projects Fall 2010
  263. quantifying cancer progression with conjunctive Bayesian networks.
  264. rOBPCA: A New Approach to Robust Principal Component Analysis
  265. regression on Manifold using Kernel Dimension Reduction
  266. relevant Component Analysis
  267. residual Component Analysis: Generalizing PCA for more flexible inference in linear-Gaussian models
  268. s13Stat946proposal
  269. sandbox to test w2l
  270. scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines
  271. schedule
  272. schedule946
  273. schedule of Project Presentations
  274. self-Taught Learning
  275. show, Attend and Tell: Neural Image Caption Generation with Visual Attention
  276. sign up for your presentation
  277. signupformStat341F11
  278. singular Value Decomposition(SVD)
  279. sparse PCA
  280. stat441F18
  281. stat441F18/TCNLM
  282. stat441F18/YOLO
  283. stat441F20
  284. stat441w18
  285. stat441w18/A New Method of Region Embedding for Text Classification
  286. stat441w18/Convolutional Neural Networks for Sentence Classification
  287. stat441w18/Image Question Answering using CNN with Dynamic Parameter Prediction
  288. stat441w18/Saliency-based Sequential Image Attention with Multiset Prediction
  289. stat441w18/e-gan
  290. stat441w18/mastering-chess-and-shogi-self-play
  291. stat441w18/summary 1
  292. stat841F18/
  293. stat946-Fall 2010
  294. stat946F18
  295. stat946F18/Autoregressive Convolutional Neural Networks for Asynchronous Time Series
  296. stat946F18/Beyond Word Importance Contextual Decomposition to Extract Interactions from LSTMs
  297. stat946F18/differentiableplasticity
  298. stat946F20
  299. stat946F20/GradientLess Descent
  300. stat946f15
  301. stat946f15/Deep neural networks for acoustic modeling in speech recognition
  302. stat946f17
  303. stat946s13
  304. stat946w18
  305. stat946w18/
  306. stat946w18/AmbientGAN: Generative Models from Lossy Measurements
  307. stat946w18/Hierarchical Representations for Efficient Architecture Search
  308. stat946w18/IMPROVING GANS USING OPTIMAL TRANSPORT
  309. stat946w18/Implicit Causal Models for Genome-wide Association Studies
  310. stat946w18/MaskRNN: Instance Level Video Object Segmentation
  311. stat946w18/Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data
  312. stat946w18/Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolutional Layers
  313. stat946w18/Self Normalizing Neural Networks
  314. stat946w18/Spectral normalization for generative adversial network
  315. stat946w18/Synthetic and natural noise both break neural machine translation
  316. stat946w18/Tensorized LSTMs
  317. stat946w18/Towards Image Understanding From Deep Compression Without Decoding
  318. stat946w18/Unsupervised Machine Translation Using Monolingual Corpora Only
  319. stat946w18/Wavelet Pooling For Convolutional Neural Networks
  320. statf09841Proposal
  321. statf09841Scribe
  322. statf10841Scribe
  323. summary
  324. supervised Dictionary Learning
  325. tRIAL for that odd behaviour
  326. techniques for Normal and Gamma Sampling
  327. the Indian Buffet Process: An Introduction and Review
  328. the Manifold Tangent Classifier
  329. the Wake-Sleep Algorithm for Unsupervised Neural Networks
  330. time-series-using-GAN
  331. very Deep Convoloutional Networks for Large-Scale Image Recognition
  332. video-Based Face Recognition Using Adaptive Hidden Markov Models
  333. visualizing Data using t-SNE
  334. visualizing Similarity Data with a Mixture of Maps
  335. what game are we playing
  336. wikicoursenote:Manual of Style
  337. wikicoursenote:cleanup

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