User contributions for Wfisher
Jump to navigation
Jump to search
28 November 2018
- 11:4111:41, 28 November 2018 diff hist 0 CapsuleNets spelling
- 11:4011:40, 28 November 2018 diff hist +1,185 CapsuleNets Add a quote from another paper describing capsules (T)
- 11:1911:19, 28 November 2018 diff hist +709 stat946F18/Autoregressive Convolutional Neural Networks for Asynchronous Time Series Add description of AR (T)
26 November 2018
- 14:0114:01, 26 November 2018 diff hist +33 policy optimization with demonstrations Misc edits (E)
25 November 2018
- 23:2623:26, 25 November 2018 diff hist +476 Visual Reinforcement Learning with Imagined Goals Add graph from results (T)
- 23:2523:25, 25 November 2018 diff hist +44 N File:WF Sec 11Nov 25 02.png Source: https://arxiv.org/pdf/1807.04742.pdf current
- 23:1723:17, 25 November 2018 diff hist +393 Visual Reinforcement Learning with Imagined Goals Add intro description of algorithm (T)
- 23:1123:11, 25 November 2018 diff hist 0 N File:WF Sec 11Nov25 01.png No edit summary current
- 23:0123:01, 25 November 2018 diff hist +483 Unsupervised Neural Machine Translation Misc Edits (T,E)
22 November 2018
- 00:1400:14, 22 November 2018 diff hist +822 conditional neural process Add some related work (T)
19 November 2018
- 11:5911:59, 19 November 2018 diff hist 0 Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction edit (E)
- 11:5711:57, 19 November 2018 diff hist −14 Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction Remove 'contrast'
- 11:5211:52, 19 November 2018 diff hist 0 Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction lower case for consistency (E)
- 11:4711:47, 19 November 2018 diff hist +2 Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction Edits (E)
- 11:2811:28, 19 November 2018 diff hist 0 Learning to Navigate in Cities Without a Map edit (E)
- 11:2011:20, 19 November 2018 diff hist +268 Learning to Navigate in Cities Without a Map Add more info and advantages (T)
- 11:1511:15, 19 November 2018 diff hist +93 Learning to Navigate in Cities Without a Map Some description of graph
- 11:1211:12, 19 November 2018 diff hist +222 Learning to Navigate in Cities Without a Map Add some description of related work (T)
- 11:0911:09, 19 November 2018 diff hist +74 Learning to Navigate in Cities Without a Map Small additions (T)
18 November 2018
- 22:4022:40, 18 November 2018 diff hist +14 Obfuscated Gradients Give a False Sense of Security Circumventing Defenses to Adversarial Examples Small edits (E)
- 21:5221:52, 18 November 2018 diff hist +191 Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias Misc additions (T,E)
- 21:4121:41, 18 November 2018 diff hist +91 Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias Add misc info (T)
- 21:3421:34, 18 November 2018 diff hist +92 Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias Add info on robot (T)
- 21:1521:15, 18 November 2018 diff hist +662 Countering Adversarial Images Using Input Transformations Misc additional info (T)
16 November 2018
- 21:1221:12, 16 November 2018 diff hist −145 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling →Value Network
- 21:1021:10, 16 November 2018 diff hist +97 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling →Weaknesses
- 21:1021:10, 16 November 2018 diff hist +169 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling →Selection
- 21:0121:01, 16 November 2018 diff hist +180 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling →Strengths
- 20:5720:57, 16 November 2018 diff hist +191 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling →Weaknesses
- 20:5520:55, 16 November 2018 diff hist +1,051 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling Add details
- 20:3520:35, 16 November 2018 diff hist +176 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling Reference curling program
- 12:4212:42, 16 November 2018 diff hist +279 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling →Weaknesses
- 12:4012:40, 16 November 2018 diff hist +342 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling →Weaknesses
- 12:3712:37, 16 November 2018 diff hist +1,249 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling Add a critique
- 12:3012:30, 16 November 2018 diff hist −15 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling →Future Work
- 12:3012:30, 16 November 2018 diff hist +716 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling Describe Results
- 12:2912:29, 16 November 2018 diff hist +58 N File:curling ratings.png Source: http://proceedings.mlr.press/v80/lee18b/lee18b.pdf current
- 12:1612:16, 16 November 2018 diff hist +2,070 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling Discuss some results
- 12:1412:14, 16 November 2018 diff hist +58 N File:curling KR test.png Source: http://proceedings.mlr.press/v80/lee18b/lee18b.pdf current
15 November 2018
- 23:3023:30, 15 November 2018 diff hist +1,077 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling Add references
- 23:2423:24, 15 November 2018 diff hist +4 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling →Supervised Learning
- 23:2023:20, 15 November 2018 diff hist −3 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling →Self-Play Reinforcement Learning
- 23:1823:18, 15 November 2018 diff hist +1,733 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling Add self-play sections
- 22:5722:57, 15 November 2018 diff hist +1,105 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling Add information on supervised learning
- 22:5322:53, 15 November 2018 diff hist +58 N File:curling loss function.png Source: http://proceedings.mlr.press/v80/lee18b/lee18b.pdf current
- 22:4222:42, 15 November 2018 diff hist +682 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling Start creating supervised learning section
- 22:3022:30, 15 November 2018 diff hist +421 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling Finish off MCTS sections
14 November 2018
- 19:3519:35, 14 November 2018 diff hist +934 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling Start describing MCTS used
- 19:2219:22, 14 November 2018 diff hist +58 N File:curling kernel equations.png Source: http://proceedings.mlr.press/v80/lee18b/lee18b.pdf current
- 19:1119:11, 14 November 2018 diff hist −42 Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling Sections