Long pages

Showing below up to 50 results in range #151 to #200.

151. (hist) ‎Robust Imitation of Diverse Behaviors ‎[20,150 bytes]
152. (hist) ‎Mask RCNN ‎[20,099 bytes]
153. (hist) ‎learning Long-Range Vision for Autonomous Off-Road Driving ‎[20,000 bytes]
154. (hist) ‎visualizing Data using t-SNE ‎[19,850 bytes]
155. (hist) ‎overfeat: integrated recognition, localization and detection using convolutional networks ‎[19,798 bytes]
156. (hist) ‎stat441F18/YOLO ‎[19,690 bytes]
157. (hist) ‎Do Deep Neural Networks Suffer from Crowding ‎[19,524 bytes]
158. (hist) ‎PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space ‎[19,470 bytes]
159. (hist) ‎Deep Residual Learning for Image Recognition ‎[19,366 bytes]
160. (hist) ‎Deep Double Descent Where Bigger Models and More Data Hurt ‎[19,133 bytes]
161. (hist) ‎stat946w18/AmbientGAN: Generative Models from Lossy Measurements ‎[19,101 bytes]
162. (hist) ‎distributed Representations of Words and Phrases and their Compositionality ‎[19,031 bytes]
163. (hist) ‎Understanding Image Motion with Group Representations ‎[18,990 bytes]
164. (hist) ‎Predicting Floor Level For 911 Calls with Neural Network and Smartphone Sensor Data ‎[18,868 bytes]
165. (hist) ‎learning Hierarchical Features for Scene Labeling ‎[18,813 bytes]
166. (hist) ‎Learning What and Where to Draw ‎[18,801 bytes]
167. (hist) ‎markov Random Fields for Super-Resolution ‎[18,723 bytes]
168. (hist) ‎stat441F18/TCNLM ‎[18,699 bytes]
169. (hist) ‎A universal SNP and small-indel variant caller using deep neural networks ‎[18,624 bytes]
170. (hist) ‎Multi-scale Dense Networks for Resource Efficient Image Classification ‎[18,397 bytes]
171. (hist) ‎generating text with recurrent neural networks ‎[18,394 bytes]
172. (hist) ‎IPBoost ‎[18,321 bytes]
173. (hist) ‎probabilistic Matrix Factorization ‎[18,287 bytes]
174. (hist) ‎compressive Sensing ‎[18,248 bytes]
175. (hist) ‎Synthesizing Programs for Images usingReinforced Adversarial Learning ‎[18,187 bytes]
176. (hist) ‎Neural Audio Synthesis of Musical Notes with WaveNet autoencoders ‎[18,174 bytes]
177. (hist) ‎stat946w18/IMPROVING GANS USING OPTIMAL TRANSPORT ‎[18,063 bytes]
178. (hist) ‎incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary) ‎[18,023 bytes]
179. (hist) ‎Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence ‎[17,860 bytes]
180. (hist) ‎on the difficulty of training recurrent neural networks ‎[17,840 bytes]
181. (hist) ‎One pixel attack for fooling deep neural networks ‎[17,832 bytes]
182. (hist) ‎THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS ‎[17,773 bytes]
183. (hist) ‎Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments ‎[17,715 bytes]
184. (hist) ‎Pixels to Graphs by Associative Embedding ‎[17,615 bytes]
185. (hist) ‎graphical models for structured classification, with an application to interpreting images of protein subcellular location patterns ‎[17,604 bytes]
186. (hist) ‎multi-Task Feature Learning ‎[17,528 bytes]
187. (hist) ‎stat946w18/Synthetic and natural noise both break neural machine translation ‎[17,403 bytes]
188. (hist) ‎proposal for STAT946 projects Fall 2010 ‎[17,366 bytes]
189. (hist) ‎Influenza Forecasting Framework based on Gaussian Processes ‎[17,358 bytes]
190. (hist) ‎F18-STAT946-Proposal ‎[17,305 bytes]
191. (hist) ‎deep Neural Nets as a Method for Quantitative Structure–Activity Relationships ‎[17,219 bytes]
192. (hist) ‎discLDA: Discriminative Learning for Dimensionality Reduction and Classification ‎[17,184 bytes]
193. (hist) ‎BERTScore: Evaluating Text Generation with BERT ‎[17,132 bytes]
194. (hist) ‎Dense Passage Retrieval for Open-Domain Question Answering ‎[17,125 bytes]
195. (hist) ‎kernelized Locality-Sensitive Hashing ‎[17,115 bytes]
196. (hist) ‎CatBoost: unbiased boosting with categorical features ‎[17,013 bytes]
197. (hist) ‎When Does Self-Supervision Improve Few-Shot Learning? ‎[16,936 bytes]
198. (hist) ‎Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition ‎[16,892 bytes]
199. (hist) ‎stat946w18/Implicit Causal Models for Genome-wide Association Studies ‎[16,805 bytes]
200. (hist) ‎DeepVO Towards end to end visual odometry with deep RNN ‎[16,676 bytes]