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Showing below up to 293 results in range #71 to #363.

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  1. F21-STAT 940-Proposal
  2. Fairness Without Demographics in Repeated Loss Minimization
  3. FeUdal Networks for Hierarchical Reinforcement Learning
  4. Fix your classifier: the marginal value of training the last weight layer
  5. From Variational to Deterministic Autoencoders
  6. Functional regularisation for continual learning with gaussian processes
  7. Generating Image Descriptions
  8. Going Deeper with Convolutions
  9. GradientLess Descent
  10. Gradient Episodic Memory for Continual Learning
  11. Graph Structure of Neural Networks
  12. Hash Embeddings for Efficient Word Representations
  13. Hierarchical Question-Image Co-Attention for Visual Question Answering
  14. Hierarchical Representations for Efficient Architecture Search
  15. IPBoost
  16. Imagination-Augmented Agents for Deep Reinforcement Learning
  17. Imagination Augmented Agents for Deep Reinforcement Learning
  18. Improving neural networks by preventing co-adaption of feature detectors
  19. Improving neural networks by preventing co-adaption of feature detectors 2020 Fall
  20. Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
  21. Influenza Forecasting Framework based on Gaussian Processes
  22. Influenza Forecasting Framework based on Gaussian processes Summary
  23. Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
  24. Learning Combinatorial Optimzation
  25. Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
  26. Learning What and Where to Draw
  27. Learning the Number of Neurons in Deep Networks
  28. Learning to Navigate in Cities Without a Map
  29. Learning to Teach
  30. LightRNN: Memory and Computation-Efficient Recurrent Neural Networks
  31. Loss Function Search for Face Recognition
  32. MULTI-VIEW DATA GENERATION WITHOUT VIEW SUPERVISION
  33. Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
  34. MarrNet: 3D Shape Reconstruction via 2.5D Sketches
  35. Mask RCNN
  36. Memory-Based Parameter Adaptation
  37. Meta-Learning-For-Domain Generalization
  38. Meta-Learning For Domain Generalization
  39. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
  40. ModelFramework.jpg
  41. Model Agnostic Learning of Semantic Features
  42. Modular Multitask Reinforcement Learning with Policy Sketches
  43. Multi-scale Dense Networks for Resource Efficient Image Classification
  44. Music Recommender System Based using CRNN
  45. Neural Audio Synthesis of Musical Notes with WaveNet autoencoders
  46. Neural ODEs
  47. Neural Speed Reading via Skim-RNN
  48. Obfuscated Gradients Give a False Sense of Security Circumventing Defenses to Adversarial Examples
  49. On The Convergence Of ADAM And Beyond
  50. One-Shot Imitation Learning
  51. One-Shot Object Detection with Co-Attention and Co-Excitation
  52. One pixel attack for fooling deep neural networks
  53. Patch Based Convolutional Neural Network for Whole Slide Tissue Image Classification
  54. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
  55. Pixels to Graphs by Associative Embedding
  56. Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence
  57. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
  58. Poison Frogs Neural Networks
  59. Pre-Training-Tasks-For-Embedding-Based-Large-Scale-Retrieval
  60. Pre-Training Tasks For Embedding-Based Large-Scale Retrieval
  61. Predicting Floor Level For 911 Calls with Neural Network and Smartphone Sensor Data
  62. Predicting Hurricane Trajectories Using a Recurrent Neural Network
  63. Proposal for STAT946 (Deep Learning) final projects Fall 2017
  64. Reinforcement Learning of Theorem Proving
  65. Representations of Words and Phrases and their Compositionality
  66. Research Papers Classification System
  67. Research on Multiple Classification Based on Improved SVM Algorithm for Balanced Binary Decision Tree
  68. Roberta
  69. Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
  70. Robust Imitation Learning from Noisy Demonstrations
  71. Robust Imitation of Diverse Behaviors
  72. Robust Probabilistic Modeling with Bayesian Data Reweighting
  73. STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study
  74. STAT946F17/Conditional Image Generation with PixelCNN Decoders
  75. STAT946F17/Decoding with Value Networks for Neural Machine Translation
  76. STAT946F17/ Automated Curriculum Learning for Neural Networks
  77. STAT946F17/ Coupled GAN
  78. STAT946F17/ Dance Dance Convolution
  79. STAT946F17/ Improved Variational Inference with Inverse Autoregressive Flow
  80. STAT946F17/ Learning Important Features Through Propagating Activation Differences
  81. STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN
  82. STAT946F17/ Teaching Machines to Describe Images via Natural Language Feedback
  83. STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
  84. Searching For Efficient Multi Scale Architectures For Dense Image Prediction
  85. Self-Supervised Learning of Pretext-Invariant Representations
  86. Semantic Relation Classification——via Convolution Neural Network
  87. ShakeDrop Regularization
  88. Speech2Face: Learning the Face Behind a Voice
  89. Spherical CNNs
  90. Streaming Bayesian Inference for Crowdsourced Classification
  91. Summary - A Neural Representation of Sketch Drawings
  92. Summary for survey of neural networked-based cancer prediction models from microarray data
  93. Summary of A Probabilistic Approach to Neural Network Pruning
  94. SuperGLUE
  95. Superhuman AI for Multiplayer Poker
  96. Surround Vehicle Motion Prediction
  97. Synthesizing Programs for Images usingReinforced Adversarial Learning
  98. THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS
  99. Task Understanding from Confushing Multitask Data
  100. Task Understanding from Confusing Multi-task Data
  101. The Curious Case of Degeneration
  102. The Detection of Black Ice Accidents Using CNNs
  103. This Looks Like That: Deep Learning for Interpretable Image Recognition
  104. Time-series Generative Adversarial Networks
  105. Towards Deep Learning Models Resistant to Adversarial Attacks
  106. Traffic Sign Recognition System (TSRS): SVM and Convolutional Neural Network
  107. Training And Inference with Integers in Deep Neural Networks
  108. U-Time:A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging Summary
  109. Understanding Image Motion with Group Representations
  110. Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
  111. Universal Style Transfer via Feature Transforms
  112. Unsupervised Domain Adaptation with Residual Transfer Networks
  113. Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness
  114. Unsupervised Machine Translation Using Monolingual Corpora Only
  115. Unsupervised Neural Machine Translation
  116. Visual Reinforcement Learning with Imagined Goals
  117. Wasserstein Auto-Encoders
  118. Wasserstein Auto-encoders
  119. Wavelet Pooling CNN
  120. When Does Self-Supervision Improve Few-Shot Learning?
  121. When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary
  122. Wide and Deep Learning for Recommender Systems
  123. Word translation without parallel data
  124. XGBoost
  125. XGBoost: A Scalable Tree Boosting System
  126. Zero-Shot Visual Imitation
  127. a Deeper Look into Importance Sampling
  128. a Direct Formulation For Sparse PCA Using Semidefinite Programming
  129. a Dynamic Bayesian Network Click Model for web search ranking
  130. a Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis
  131. a Rank Minimization Heuristic with Application to Minimum Order System Approximation
  132. a fair comparison of graph neural networks for graph classification
  133. a fast learning algorithm for deep belief nets
  134. a neural representation of sketch drawings
  135. adaptive dimension reduction for clustering high dimensional data
  136. again on Markov Chain
  137. bayesian and Frequentist Schools of Thought
  138. binomial Probability Monte Carlo Sampling June 2 2009
  139. compressive Sensing
  140. conditional neural process
  141. consistency of Trace Norm Minimization
  142. context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
  143. contributions on Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
  144. contributions on Quantifying Cancer Progression with Conjunctive Bayesian Networks
  145. contributions on Video-Based Face Recognition Using Adaptive Hidden Markov Models
  146. copyofstat341
  147. decentralised Data Fusion: A Graphical Model Approach (Summary)
  148. deepGenerativeModels
  149. deep Convolutional Neural Networks For LVCSR
  150. deep Learning of the tissue-regulated splicing code
  151. deep neural networks for acoustic modeling in speech recognition
  152. deflation Method for Penalized Matrix Decomposition Sparse PCA
  153. deflation Methods for Sparse PCA
  154. dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
  155. discLDA: Discriminative Learning for Dimensionality Reduction and Classification
  156. distributed Representations of Words and Phrases and their Compositionality
  157. f11Stat841EditorSignUp
  158. f11Stat841presentation
  159. f11Stat841proposal
  160. f11Stat946papers
  161. f11Stat946presentation
  162. f11stat946EditorSignUp
  163. f14Stat842EditorSignUp
  164. f15Stat946PaperSignUp
  165. f17Stat946PaperSignUp
  166. generating Random Numbers
  167. genetics
  168. hamming Distance Metric Learning
  169. hierarchical Dirichlet Processes
  170. importance Sampling June 2 2009
  171. importance Sampling and Markov Chain Monte Carlo (MCMC)
  172. importance Sampling and Monte Carlo Simulation
  173. incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary)
  174. independent Component Analysis: algorithms and applications
  175. is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction
  176. kernel Dimension Reduction in Regression
  177. kernel Spectral Clustering for Community Detection in Complex Networks
  178. kernelized Locality-Sensitive Hashing
  179. kernelized Sorting
  180. learn what not to learn
  181. learning2reasoning
  182. learning Convolutional Feature Hierarchies for Visual Recognition
  183. learning Fast Approximations of Sparse Coding
  184. learning Spectral Clustering, With Application To Speech Separation
  185. learning a Nonlinear Embedding by Preserving Class Neighborhood Structure
  186. link to my paper
  187. mULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION
  188. main Page
  189. mark Your Contribution here
  190. mark your contribution here
  191. markov Chain Definitions
  192. matrix Completion with Noise
  193. maximum-Margin Matrix Factorization
  194. maximum Variance Unfolding (June 2 2009)
  195. maximum likelihood estimation of intrinsic dimension
  196. meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
  197. measuring Statistical Dependence with Hilbert-Schmidt Norm
  198. measuring and testing dependence by correlation of distances
  199. monte Carlo Integration
  200. monte Carlo methods
  201. neighbourhood Components Analysis
  202. neural Machine Translation: Jointly Learning to Align and Translate
  203. nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization
  204. nonparametric Latent Feature Models for Link Prediction
  205. on using very large target vocabulary for neural machine translation
  206. orthogonal gradient descent for continual learning
  207. overfeat: integrated recognition, localization and detection using convolutional networks
  208. paper 13
  209. paper Summaries
  210. policy optimization with demonstrations
  211. proof
  212. proof of Lemma 1
  213. proof of Theorem 1
  214. proposal Fall 2010
  215. proposal for STAT946 (Deep Learning) final projects Fall 2015
  216. proposal for STAT946 projects
  217. proposal for STAT946 projects Fall 2010
  218. quantifying cancer progression with conjunctive Bayesian networks.
  219. rOBPCA: A New Approach to Robust Principal Component Analysis
  220. regression on Manifold using Kernel Dimension Reduction
  221. relevant Component Analysis
  222. residual Component Analysis: Generalizing PCA for more flexible inference in linear-Gaussian models
  223. s13Stat946proposal
  224. sandbox to test w2l
  225. scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines
  226. schedule
  227. schedule946
  228. schedule of Project Presentations
  229. self-Taught Learning
  230. show, Attend and Tell: Neural Image Caption Generation with Visual Attention
  231. sign up for your presentation
  232. signupformStat341F11
  233. singular Value Decomposition(SVD)
  234. sparse PCA
  235. stat441F18
  236. stat441F18/TCNLM
  237. stat441F18/YOLO
  238. stat441F21
  239. stat441w18
  240. stat441w18/A New Method of Region Embedding for Text Classification
  241. stat441w18/Convolutional Neural Networks for Sentence Classification
  242. stat441w18/Image Question Answering using CNN with Dynamic Parameter Prediction
  243. stat441w18/Saliency-based Sequential Image Attention with Multiset Prediction
  244. stat441w18/e-gan
  245. stat441w18/mastering-chess-and-shogi-self-play
  246. stat441w18/summary 1
  247. stat841F18/
  248. stat940F21
  249. stat946-Fall 2010
  250. stat946F18
  251. stat946F18/Autoregressive Convolutional Neural Networks for Asynchronous Time Series
  252. stat946F18/Beyond Word Importance Contextual Decomposition to Extract Interactions from LSTMs
  253. stat946F18/differentiableplasticity
  254. stat946F20/GradientLess Descent
  255. stat946f15
  256. stat946f15/Deep neural networks for acoustic modeling in speech recognition
  257. stat946f17
  258. stat946s13
  259. stat946w18
  260. stat946w18/
  261. stat946w18/AmbientGAN: Generative Models from Lossy Measurements
  262. stat946w18/Hierarchical Representations for Efficient Architecture Search
  263. stat946w18/IMPROVING GANS USING OPTIMAL TRANSPORT
  264. stat946w18/Implicit Causal Models for Genome-wide Association Studies
  265. stat946w18/MaskRNN: Instance Level Video Object Segmentation
  266. stat946w18/Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data
  267. stat946w18/Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolutional Layers
  268. stat946w18/Self Normalizing Neural Networks
  269. stat946w18/Spectral normalization for generative adversial network
  270. stat946w18/Synthetic and natural noise both break neural machine translation
  271. stat946w18/Tensorized LSTMs
  272. stat946w18/Towards Image Understanding From Deep Compression Without Decoding
  273. stat946w18/Unsupervised Machine Translation Using Monolingual Corpora Only
  274. stat946w18/Wavelet Pooling For Convolutional Neural Networks
  275. statf09841Proposal
  276. statf09841Scribe
  277. statf10841Scribe
  278. summary
  279. supervised Dictionary Learning
  280. tRIAL for that odd behaviour
  281. techniques for Normal and Gamma Sampling
  282. test
  283. the Indian Buffet Process: An Introduction and Review
  284. the Manifold Tangent Classifier
  285. the Wake-Sleep Algorithm for Unsupervised Neural Networks
  286. time-series-using-GAN
  287. very Deep Convoloutional Networks for Large-Scale Image Recognition
  288. video-Based Face Recognition Using Adaptive Hidden Markov Models
  289. visualizing Data using t-SNE
  290. visualizing Similarity Data with a Mixture of Maps
  291. what game are we playing
  292. wikicoursenote:Manual of Style
  293. wikicoursenote:cleanup

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