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Search Results - Showing 12 - 24 Of 33
[MMD] Galaxias! (Kamui Gakupo & Megurine Luka)
⏲ 89 sec ✓ 28-Sep-2012
Woody - Fashion Underwear W17 Collection
⏲ 3 minutes 2 seconds 👁 54.5K
Russia's Extreme Teen Model Factory | Reggie Yates Extreme | Real Stories
⏲ 57 minutes 27 seconds 👁 1.2M
Ilya & Olga - A Very Non-Wedding (Shorter Version)
⏲ 1 min 6 sec ✓ 14-Aug-2015
Young Model •
⏲ 2 minutes 15 seconds 👁 26.1K
paranormal session: backstage
⏲ 1 min 64 sec ✓ 24-Jul-2017
Ilya & Olga - A Very Non-Wedding - 1 Year Married
⏲ 1 min 22 sec ✓ 09-Aug-2015
Residual-based Neural Network Solution of 1Dt Advection-Diffusion PDE - Low Peclet number
⏲ 13 sec ✓ 25-Jul-2019
Neural Network Solution of 2Dt Advection-Diffusion PDE
⏲ 10 sec ✓ 26-Jul-2019
Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation
⏲ 9 min 34 sec ✓ 17-Jan-2020
Neural Network Solution of 1Dt Advection-Diffusion PDE - Low Peclet number
⏲ 12 sec ✓ 06-Apr-2019
Machine Learning Racing AI - based on NNs trained with entirely synthetic data (car and track models from PoD '96)
⏲ 1 min 64 sec ✓ 18-Jul-2020
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_mmd-galaxias-kamui-gakupo-amp-megurine-luka.webp "This is my first MMD video. Hope that you like it n_nnnModels:nSong: GalaxiasnPD Luka by bookazoid & AndreehXDnPD Gackpoid by Majikaru-RinnStage: ???nMotion: Female by ボカペラP, Male by ちゃむnnLuka model is on deviantart.nGakupo model is not redistributed anymore, sorry :(")
_woody-fashion-underwear-w17-collection.webp "Woody Turkiye")
_russia39s-extreme-teen-model-factory-124-reggie-yates-extreme-124-real-stories.webp "Real Stories")
_ilya-amp-olga-a-very-non-wedding-shorter-version.webp "Dir Artem Korchagin @korchagin_artemnProducer Marina Larskaya @larskayanMUAH Natalia Malova & PURPUR Beauty @malovamakeup @purpur_beautynModels Ilya and Olga Navdaevy @id34884809 & @obednovanInteriors Loft Stalinka studio, New Tales wedding agency @loft_stalinka @new_tale.nnnBackstage Daria Sharkova @godaria, Andrey Kashurin @andreykashurinnFor Cinematique video school @shkolavideo52 (shkolavideo.ru)")
_young-model.webp "Mujeres, Música y Canciones")
_paranormal-session-backstage.webp "#paranormalnph @gaidukdenisnstyle @nataly_kosmosnhair @ilyashuvalov_nn & @prostoe @soho_style_runmua @skvorec_makeup @purpurbeautynmodels @elenabelihina & @kris.dreamer @premierart_modelagencynclothing @intro_versionnjewerly @annakopanlocation @ncca_arsenalnvideo @franky_dreams")
_ilya-amp-olga-a-very-non-wedding-1-year-married.webp "Dir Artem Korchagin @korchagin_artemnProducer Marina Larskaya @larskayanMUAH Natalia Malova & PURPUR Beauty @malovamakeup @purpur_beautynModels Ilya and Olga Navdaevy @id34884809 & @obednovanInteriors Loft Stalinka studio, New Tales wedding agency @loft_stalinka @new_tale.nnnBackstage Daria Sharkova @godaria, Andrey Kashurin @andreykashurinnFor Cinematique video school @shkolavideo52 (shkolavideo.ru)")
_residual-based-neural-network-solution-of-1dt-advection-diffusion-pde-low-peclet-number.webp "VarNet: Variational Neural Networks for the Solution of Partial Differential Equationsnhttps://arxiv.org/pdf/1912.07443.pdfnnAuthors: Reza Khodayi-mehr and Michael M. ZavlanosnnDescription: This video shows the solution of a benchmark 1D time-dependent Advection-Diffusion PDE for low Peclet number obtained using the PDE-residual instead of the variational method proposed in the paper. Note that there is considerable error in capturing the solution and boundary conditions when PDE-residual is use")
_neural-network-solution-of-2dt-advection-diffusion-pde.webp "VarNet: Variational Neural Networks for the Solution of Partial Differential Equationsnhttps://arxiv.org/pdf/1912.07443.pdfnnAuthors: Reza Khodayi-mehr and Michael M. ZavlanosnnDescription: This video shows the solution of a benchmark 2D time-dependent Advection-Diffusion PDE obtained using the VarNet library. This solution corresponds to a highly advective case for which the discretization-based methods require very fine grids.nnAbstract: In this paper we propose a new model-based unsupervised")
_language-modelling-makes-sense-propagating-representations-throughwordnet-for-full-coverage-word-sense-disambiguation.webp "Authors: Daniel Loureiro, Alípio JorgennContextual embeddings represent a new generation of semantic representations learned from Neural Language Modelling (NLM) that addresses the issue of meaning conflation hampering traditional word embeddings. In this work, we show that contextual embeddings can be used to achieve unprecedented gains in Word Sense Disambiguation (WSD) tasks. Our approach focuses on creating sense-level embeddings with full-coverage of WordNet, and without recourse to expli")
_neural-network-solution-of-1dt-advection-diffusion-pde-low-peclet-number.webp "VarNet: Variational Neural Networks for the Solution of Partial Differential Equationsnhttps://arxiv.org/pdf/1912.07443.pdfnnAuthors: Reza Khodayi-mehr and Michael M. ZavlanosnnnDescription: This video shows the solution of a benchmark 1D time-dependent Advection-Diffusion PDE for low Peclet number obtained using the VarNet library. The solution is compared to the analytical solution in the left panel.nnAbstract: In this paper we propose a new model-based unsupervised learning method, called Var")
_machine-learning-racing-ai-based-on-nns-trained-with-entirely-synthetic-data-car-and-track-models-from-pod-3996.webp "Race between five Machine Learning based AI agents.nnTrack and Car models are borrowed from PoD (1996).nnThe controllers are based around a NN that predicts maximum speeds from track geometry, while following a (procedural) pre-defined racing line.nnThe cars are following paths randomly interpolated between the Minimum Curvature Path and Shortest Path of the track, found using a factor-graph based optimiser.nnThe NN is trained with entirely synthetic data by having a simple algorithm find the fa")
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