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Showing below up to 250 results in range #21 to #270.

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

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