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Showing below up to 250 results in range #31 to #280.

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

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