File:AI Attention imaging – Attention Profiles of continuous-time neural networks.webp
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Captions
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From the study "Closed-form continuous-time neural networks"
Summary
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| Description |
English: "Trained networks receive unseen inputs (first column in each tab) and generate acceleration and steering commands. We use the Visual-Backprop algorithm65 to compute the saliency maps of the convolutional part of each network. a) results for networks tested on data collected in summer. b) results for networks tested on data collected in winter. c) results for inputs corrupted by a zero-mean Gaussian noise with variance, σ2 = 0.35." |
| Date | |
| Source | https://www.nature.com/articles/s42256-022-00556-7 |
| Author | Authors of the study: Ramin Hasani, Mathias Lechner, Alexander Amini, Lucas Liebenwein, Aaron Ray, Max Tschaikowski, Gerald Teschl & Daniela Rus |
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This file is licensed under the Creative Commons Attribution 4.0 International license.
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
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| current | 20:56, 9 June 2024 | | 1,585 × 1,405 (168 KB) | Prototyperspective (talk | contribs) | Uploaded a work by Authors of the study: Ramin Hasani, Mathias Lechner, Alexander Amini, Lucas Liebenwein, Aaron Ray, Max Tschaikowski, Gerald Teschl & Daniela Rus from https://www.nature.com/articles/s42256-022-00556-7 with UploadWizard |
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