Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Martin Riedmiller

Showing results (1-10 of 7) with videos related to

Pageof 1
Sort By:
Frontiers in Psychology|October 19, 2013
Modeling effects of intrinsic and extrinsic rewards on the competition between striatal learning systemsJoschka Boedecker, Thomas Lampe, Martin Riedmiller
Biological Cybernetics|December 18, 2008
Computational object recognition: a biologically motivated approachTim C Kietzmann, Sascha Lange, Martin Riedmiller
IEEE Transactions on Pattern Analysis and Machine Intelligence|November 6, 2015
Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural NetworksAlexey Dosovitskiy, Philipp Fischer, Jost Tobias Springenberg, et al.
Plos Computational Biology|August 11, 2016
Autonomous Optimization of Targeted Stimulation of Neuronal NetworksSreedhar S Kumar, Jan Wülfing, Samora Okujeni, et al.
Nature|February 27, 2015
Human-level control through deep reinforcement learningVolodymyr Mnih, Koray Kavukcuoglu, David Silver, et al.
Nature|February 17, 2022
Magnetic control of tokamak plasmas through deep reinforcement learningJonas Degrave, Federico Felici, Jonas Buchli, et al.
Science (New York, N.Y.)|September 4, 2025
Improving cosmological reach of a gravitational wave observatory using Deep Loop ShapingJonas Buchli, Brendan Tracey, Tomislav Andric, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Frontiers in Psychology|October 19, 2013
Modeling effects of intrinsic and extrinsic rewards on the competition between striatal learning systemsJoschka Boedecker, Thomas Lampe, Martin Riedmiller
Biological Cybernetics|December 18, 2008
Computational object recognition: a biologically motivated approachTim C Kietzmann, Sascha Lange, Martin Riedmiller
IEEE Transactions on Pattern Analysis and Machine Intelligence|November 6, 2015
Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural NetworksAlexey Dosovitskiy, Philipp Fischer, Jost Tobias Springenberg, et al.
Plos Computational Biology|August 11, 2016
Autonomous Optimization of Targeted Stimulation of Neuronal NetworksSreedhar S Kumar, Jan Wülfing, Samora Okujeni, et al.
Nature|February 27, 2015
Human-level control through deep reinforcement learningVolodymyr Mnih, Koray Kavukcuoglu, David Silver, et al.
Nature|February 17, 2022
Magnetic control of tokamak plasmas through deep reinforcement learningJonas Degrave, Federico Felici, Jonas Buchli, et al.
Science (New York, N.Y.)|September 4, 2025
Improving cosmological reach of a gravitational wave observatory using Deep Loop ShapingJonas Buchli, Brendan Tracey, Tomislav Andric, et al.
Pageof 1