User contributions for Wfisher

For Wfisher talk block log uploads logs

A user with 96 edits. Account created on 15 October 2018.

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10:4110:41, 28 November 2018 diff hist 0‎ CapsuleNets ‎ spelling
10:4010:40, 28 November 2018 diff hist +1,185‎ CapsuleNets ‎ Add a quote from another paper describing capsules (T)
10:1910:19, 28 November 2018 diff hist +709‎ stat946F18/Autoregressive Convolutional Neural Networks for Asynchronous Time Series ‎ Add description of AR (T)

13:0113:01, 26 November 2018 diff hist +33‎ policy optimization with demonstrations ‎ Misc edits (E)

22:2622:26, 25 November 2018 diff hist +476‎ Visual Reinforcement Learning with Imagined Goals ‎ Add graph from results (T)
22:2522:25, 25 November 2018 diff hist +44‎ N File:WF Sec 11Nov 25 02.png ‎ Source: https://arxiv.org/pdf/1807.04742.pdf current
22:1722:17, 25 November 2018 diff hist +393‎ Visual Reinforcement Learning with Imagined Goals ‎ Add intro description of algorithm (T)
22:1122:11, 25 November 2018 diff hist 0‎ N File:WF Sec 11Nov25 01.png ‎No edit summary current
22:0122:01, 25 November 2018 diff hist +483‎ Unsupervised Neural Machine Translation ‎ Misc Edits (T,E)

23:1423:14, 21 November 2018 diff hist +822‎ conditional neural process ‎ Add some related work (T)

10:5910:59, 19 November 2018 diff hist 0‎ Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction ‎ edit (E)
10:5710:57, 19 November 2018 diff hist −14‎ Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction ‎ Remove 'contrast'
10:5210:52, 19 November 2018 diff hist 0‎ Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction ‎ lower case for consistency (E)
10:4710:47, 19 November 2018 diff hist +2‎ Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction ‎ Edits (E)
10:2810:28, 19 November 2018 diff hist 0‎ Learning to Navigate in Cities Without a Map ‎ edit (E)
10:2010:20, 19 November 2018 diff hist +268‎ Learning to Navigate in Cities Without a Map ‎ Add more info and advantages (T)
10:1510:15, 19 November 2018 diff hist +93‎ Learning to Navigate in Cities Without a Map ‎ Some description of graph
10:1210:12, 19 November 2018 diff hist +222‎ Learning to Navigate in Cities Without a Map ‎ Add some description of related work (T)
10:0910:09, 19 November 2018 diff hist +74‎ Learning to Navigate in Cities Without a Map ‎ Small additions (T)

21:4021:40, 18 November 2018 diff hist +14‎ Obfuscated Gradients Give a False Sense of Security Circumventing Defenses to Adversarial Examples ‎ Small edits (E)
20:5220:52, 18 November 2018 diff hist +191‎ Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias ‎ Misc additions (T,E)
20:4120:41, 18 November 2018 diff hist +91‎ Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias ‎ Add misc info (T)
20:3420:34, 18 November 2018 diff hist +92‎ Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias ‎ Add info on robot (T)
20:1520:15, 18 November 2018 diff hist +662‎ Countering Adversarial Images Using Input Transformations ‎ Misc additional info (T)

20:1220:12, 16 November 2018 diff hist −145‎ Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling ‎ →‎Value Network
20:1020:10, 16 November 2018 diff hist +97‎ Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling ‎ →‎Weaknesses
20:1020:10, 16 November 2018 diff hist +169‎ Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling ‎ →‎Selection
20:0120:01, 16 November 2018 diff hist +180‎ Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling ‎ →‎Strengths
19:5719:57, 16 November 2018 diff hist +191‎ Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling ‎ →‎Weaknesses
19:5519:55, 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
19:3519:35, 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
11:4211:42, 16 November 2018 diff hist +279‎ Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling ‎ →‎Weaknesses
11:4011:40, 16 November 2018 diff hist +342‎ Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling ‎ →‎Weaknesses
11:3711:37, 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
11:3011:30, 16 November 2018 diff hist −15‎ Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling ‎ →‎Future Work
11:3011:30, 16 November 2018 diff hist +716‎ Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling ‎ Describe Results
11:2911:29, 16 November 2018 diff hist +58‎ N File:curling ratings.png ‎ Source: http://proceedings.mlr.press/v80/lee18b/lee18b.pdf current
11:1611:16, 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
11:1411:14, 16 November 2018 diff hist +58‎ N File:curling KR test.png ‎ Source: http://proceedings.mlr.press/v80/lee18b/lee18b.pdf current

22:3022:30, 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
22:2422:24, 15 November 2018 diff hist +4‎ Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling ‎ →‎Supervised Learning
22:2022:20, 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
22:1822:18, 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
21:5721:57, 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
21:5321:53, 15 November 2018 diff hist +58‎ N File:curling loss function.png ‎ Source: http://proceedings.mlr.press/v80/lee18b/lee18b.pdf current
21:4221:42, 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
21:3021:30, 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

18:3518:35, 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
18:2218:22, 14 November 2018 diff hist +58‎ N File:curling kernel equations.png ‎ Source: http://proceedings.mlr.press/v80/lee18b/lee18b.pdf current
18:1118:11, 14 November 2018 diff hist −42‎ Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling ‎ Sections

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