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

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

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