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

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