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  1. Deep Residual Learning for Image Recognition Summary
  2. Deep Transfer Learning with Joint Adaptation Networks
  3. Dense Passage Retrieval for Open-Domain Question Answering
  4. Depthwise Convolution Is All You Need for Learning Multiple Visual Domains
  5. Describtion of Text Mining
  6. Dialog-based Language Learning
  7. Do Deep Neural Networks Suffer from Crowding
  8. Do Vision Transformers See Like CNN
  9. Don't Just Blame Over-parametrization
  10. Don't Just Blame Over-parametrization Summary
  11. Dynamic Routing Between Capsules
  12. Dynamic Routing Between Capsules STAT946
  13. Dynamic Routing Between Capsulesl
  14. Efficient kNN Classification with Different Numbers of Nearest Neighbors
  15. End-to-End Differentiable Adversarial Imitation Learning
  16. End to end Active Object Tracking via Reinforcement Learning
  17. Evaluating Machine Accuracy on ImageNet
  18. Extreme Multi-label Text Classification
  19. F18-STAT841-Proposal
  20. F18-STAT946-Proposal
  21. F21-STAT 441/841 CM 763-Proposal
  22. F21-STAT 940-Proposal
  23. Fairness Without Demographics in Repeated Loss Minimization
  24. FeUdal Networks for Hierarchical Reinforcement Learning
  25. Fix your classifier: the marginal value of training the last weight layer
  26. From Variational to Deterministic Autoencoders
  27. Functional regularisation for continual learning with gaussian processes
  28. Generating Image Descriptions
  29. Going Deeper with Convolutions
  30. GradientLess Descent
  31. Gradient Episodic Memory for Continual Learning
  32. Graph Structure of Neural Networks
  33. Hash Embeddings for Efficient Word Representations
  34. Hierarchical Question-Image Co-Attention for Visual Question Answering
  35. Hierarchical Representations for Efficient Architecture Search
  36. How To Find The Perfect Porn Stars On The Internet
  37. IPBoost
  38. Imagination-Augmented Agents for Deep Reinforcement Learning
  39. Imagination Augmented Agents for Deep Reinforcement Learning
  40. Improving neural networks by preventing co-adaption of feature detectors
  41. Improving neural networks by preventing co-adaption of feature detectors 2020 Fall
  42. Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
  43. Influenza Forecasting Framework based on Gaussian Processes
  44. Influenza Forecasting Framework based on Gaussian processes Summary
  45. Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
  46. Learning Combinatorial Optimzation
  47. Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
  48. Learning What and Where to Draw
  49. Learning the Number of Neurons in Deep Networks
  50. Learning to Navigate in Cities Without a Map
  51. Learning to Teach
  52. LightRNN: Memory and Computation-Efficient Recurrent Neural Networks
  53. Loss Function Search for Face Recognition
  54. MULTI-VIEW DATA GENERATION WITHOUT VIEW SUPERVISION
  55. Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
  56. MarrNet: 3D Shape Reconstruction via 2.5D Sketches
  57. Mask RCNN
  58. Memory-Based Parameter Adaptation
  59. Meta-Learning-For-Domain Generalization
  60. Meta-Learning For Domain Generalization
  61. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
  62. ModelFramework.jpg
  63. Model Agnostic Learning of Semantic Features
  64. Modular Multitask Reinforcement Learning with Policy Sketches
  65. Multi-scale Dense Networks for Resource Efficient Image Classification
  66. Music Recommender System Based using CRNN
  67. Neural Audio Synthesis of Musical Notes with WaveNet autoencoders
  68. Neural ODEs
  69. Neural Speed Reading via Skim-RNN
  70. Obfuscated Gradients Give a False Sense of Security Circumventing Defenses to Adversarial Examples
  71. On The Convergence Of ADAM And Beyond
  72. One-Shot Imitation Learning
  73. One-Shot Object Detection with Co-Attention and Co-Excitation
  74. One pixel attack for fooling deep neural networks
  75. Patch Based Convolutional Neural Network for Whole Slide Tissue Image Classification
  76. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
  77. Pixels to Graphs by Associative Embedding
  78. Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence
  79. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
  80. Poison Frogs Neural Networks
  81. Pre-Training-Tasks-For-Embedding-Based-Large-Scale-Retrieval
  82. Pre-Training Tasks For Embedding-Based Large-Scale Retrieval
  83. Predicting Floor Level For 911 Calls with Neural Network and Smartphone Sensor Data
  84. Predicting Hurricane Trajectories Using a Recurrent Neural Network
  85. Proposal for STAT946 (Deep Learning) final projects Fall 2017
  86. Reinforcement Learning of Theorem Proving
  87. Representations of Words and Phrases and their Compositionality
  88. Research Papers Classification System
  89. Research on Multiple Classification Based on Improved SVM Algorithm for Balanced Binary Decision Tree
  90. Roberta
  91. Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
  92. Robust Imitation Learning from Noisy Demonstrations
  93. Robust Imitation of Diverse Behaviors
  94. Robust Probabilistic Modeling with Bayesian Data Reweighting
  95. STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study
  96. STAT946F17/Conditional Image Generation with PixelCNN Decoders
  97. STAT946F17/Decoding with Value Networks for Neural Machine Translation
  98. STAT946F17/ Automated Curriculum Learning for Neural Networks
  99. STAT946F17/ Coupled GAN
  100. STAT946F17/ Dance Dance Convolution
  101. STAT946F17/ Improved Variational Inference with Inverse Autoregressive Flow
  102. STAT946F17/ Learning Important Features Through Propagating Activation Differences
  103. STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN
  104. STAT946F17/ Teaching Machines to Describe Images via Natural Language Feedback
  105. STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
  106. Searching For Efficient Multi Scale Architectures For Dense Image Prediction
  107. Self-Supervised Learning of Pretext-Invariant Representations
  108. Semantic Relation Classification——via Convolution Neural Network
  109. ShakeDrop Regularization
  110. Speech2Face: Learning the Face Behind a Voice
  111. Spherical CNNs
  112. Streaming Bayesian Inference for Crowdsourced Classification
  113. Summary - A Neural Representation of Sketch Drawings
  114. Summary for survey of neural networked-based cancer prediction models from microarray data
  115. Summary of A Probabilistic Approach to Neural Network Pruning
  116. SuperGLUE
  117. Superhuman AI for Multiplayer Poker
  118. Surround Vehicle Motion Prediction
  119. Synthesizing Programs for Images usingReinforced Adversarial Learning
  120. THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS
  121. Task Understanding from Confushing Multitask Data
  122. Task Understanding from Confusing Multi-task Data
  123. The 10 Most Scariest Things About Accident Attorneys Near Me
  124. The Curious Case of Degeneration
  125. The Detection of Black Ice Accidents Using CNNs
  126. This Looks Like That: Deep Learning for Interpretable Image Recognition
  127. Time-series Generative Adversarial Networks
  128. Towards Deep Learning Models Resistant to Adversarial Attacks
  129. Traffic Sign Recognition System (TSRS): SVM and Convolutional Neural Network
  130. Training And Inference with Integers in Deep Neural Networks
  131. U-Time:A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging Summary
  132. Understanding Image Motion with Group Representations
  133. Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
  134. Universal Style Transfer via Feature Transforms
  135. Unsupervised Domain Adaptation with Residual Transfer Networks
  136. Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness
  137. Unsupervised Machine Translation Using Monolingual Corpora Only
  138. Unsupervised Neural Machine Translation
  139. Visual Reinforcement Learning with Imagined Goals
  140. Wasserstein Auto-Encoders
  141. Wasserstein Auto-encoders
  142. Wavelet Pooling CNN
  143. When Does Self-Supervision Improve Few-Shot Learning?
  144. When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary
  145. Wide and Deep Learning for Recommender Systems
  146. Word translation without parallel data
  147. XGBoost
  148. XGBoost: A Scalable Tree Boosting System
  149. Zero-Shot Visual Imitation
  150. a Deeper Look into Importance Sampling
  151. a Direct Formulation For Sparse PCA Using Semidefinite Programming
  152. a Dynamic Bayesian Network Click Model for Web Search Ranking
  153. a Dynamic Bayesian Network Click Model for web search ranking
  154. a New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
  155. a Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis
  156. a Rank Minimization Heuristic with Application to Minimum Order System Approximation
  157. a fair comparison of graph neural networks for graph classification
  158. a fast learning algorithm for deep belief nets
  159. a neural representation of sketch drawings
  160. acceptance-Rejection Sampling
  161. adaptive dimension reduction for clustering high dimensional data
  162. again on Markov Chain
  163. an HDP-HMM for Systems with State Persistence
  164. bayesian and Frequentist Schools of Thought
  165. binomial Probability Monte Carlo Sampling June 2 2009
  166. cardinality Restricted Boltzmann Machines
  167. compressed Sensing Reconstruction via Belief Propagation
  168. compressive Sensing
  169. compressive Sensing (Candes)
  170. conditional neural process
  171. consistency of Trace Norm Minimization
  172. context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
  173. continuous space language models
  174. contributions on Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
  175. contributions on Quantifying Cancer Progression with Conjunctive Bayesian Networks
  176. contributions on Video-Based Face Recognition Using Adaptive Hidden Markov Models
  177. convex and Semi Nonnegative Matrix Factorization
  178. copyofstat341
  179. decentralised Data Fusion: A Graphical Model Approach (Summary)
  180. deepGenerativeModels
  181. deep Convolutional Neural Networks For LVCSR
  182. deep Generative Stochastic Networks Trainable by Backprop
  183. deep Learning of the tissue-regulated splicing code
  184. deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
  185. deep Sparse Rectifier Neural Networks
  186. deep neural networks for acoustic modeling in speech recognition
  187. deflation Method for Penalized Matrix Decomposition Sparse PCA
  188. deflation Methods for Sparse PCA
  189. dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
  190. discLDA: Discriminative Learning for Dimensionality Reduction and Classification
  191. distributed Representations of Words and Phrases and their Compositionality
  192. dropout
  193. extracting and Composing Robust Features with Denoising Autoencoders
  194. f10 Stat841 digest
  195. f11Stat841EditorSignUp
  196. f11Stat841presentation
  197. f11Stat841proposal
  198. f11Stat946ass
  199. f11Stat946papers
  200. f11Stat946presentation
  201. f11stat946EditorSignUp
  202. f14Stat842EditorSignUp
  203. f15Stat946PaperSignUp
  204. f17Stat946PaperSignUp
  205. from Machine Learning to Machine Reasoning
  206. generating Random Numbers
  207. generating text with recurrent neural networks
  208. genetics
  209. goingDeeperWithConvolutions
  210. graph Laplacian Regularization for Larg-Scale Semidefinite Programming
  211. graphical models for structured classification, with an application to interpreting images of protein subcellular location patterns
  212. graves et al., Speech recognition with deep recurrent neural networks
  213. hamming Distance Metric Learning
  214. hierarchical Dirichlet Processes
  215. human-level control through deep reinforcement learning
  216. imageNet Classification with Deep Convolutional Neural Networks
  217. importance Sampling June 2 2009
  218. importance Sampling and Markov Chain Monte Carlo (MCMC)
  219. importance Sampling and Monte Carlo Simulation
  220. incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary)
  221. independent Component Analysis: algorithms and applications
  222. inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method
  223. infoboxtest
  224. is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction
  225. joint training of a convolutional network and a graphical model for human pose estimation
  226. kernel Dimension Reduction in Regression
  227. kernel Spectral Clustering for Community Detection in Complex Networks
  228. kernelized Locality-Sensitive Hashing
  229. kernelized Sorting
  230. large-Scale Supervised Sparse Principal Component Analysis
  231. learn what not to learn
  232. learning2reasoning
  233. learning Convolutional Feature Hierarchies for Visual Recognition
  234. learning Fast Approximations of Sparse Coding
  235. learning Hierarchical Features for Scene Labeling
  236. learning Long-Range Vision for Autonomous Off-Road Driving
  237. learning Phrase Representations
  238. learning Spectral Clustering, With Application To Speech Separation
  239. learning a Nonlinear Embedding by Preserving Class Neighborhood Structure
  240. link to my paper
  241. mULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION
  242. main Page
  243. mark Your Contribution here
  244. mark your contribution here
  245. markov Chain Definitions
  246. markov Random Fields for Super-Resolution
  247. matrix Completion with Noise
  248. maximum-Margin Matrix Factorization
  249. maximum Variance Unfolding (June 2 2009)
  250. maximum likelihood estimation of intrinsic dimension

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