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Neural Network Solution of 1Dt Advection-Diffusion PDE - Low Peclet number
⏲ 12 sec ✓ 06-Apr-2019
protect.me - new model for accident insurance
⏲ 1 min 20 sec ✓ 19-Oct-2018
OPPOSITE shoes TVC 30\
⏲ 30 sec ✓ 03-Jun-2021
2014 J 88 Hull #37 Available For Sale.Offered by Karma Yacht Sales
⏲ 1 min 46 sec ✓ 30-Jul-2017
Deep Learning for Robotic Mass Transport Cloaking
⏲ 13 sec ✓ 21-Sep-2018
Askhab
⏲ 53 sec ✓ 16-Jun-2023
Neural Network Solution of 1Dt Advection-Diffusion PDE - High Peclet number
⏲ 12 sec ✓ 06-Apr-2019
ACT26NOV-B Yesha present 3NN Model
⏲ 27 min 57 sec ✓ 06-Dec-2020
protect.me - New model for accident insurance_long
⏲ 3 min 69 sec ✓ 29-Mar-2019
Morphozoic Update (10-15) by Tom Portegys
⏲ 18 min 26 sec ✓ 05-Oct-2015
SILO: Emmanuel Abbe
⏲ 35 min 17 sec ✓ 18-Aug-2021
Viper 400 - Black
⏲ 53 sec ✓ 19-Feb-2022
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_silo-emmanuel-abbe.jpg "Date: 2021-04-21nnTitle: Fundamental limits of (S)GD on neural networksnnAbstract: We consider the learning paradigm consisting of training general neural networks (NN) with (S)GD. What is the class of functions that can be learned with this paradigm? How does it compare to known classes such as PAC and SQ? Is depth/overapametrization needed to learn certain classes? We show that SGD on NN is equivalent to PAC while GD on NN is equivalent to SQ, obtaining a separation between the classes learned")
_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")
_protect-me-new-model-for-accident-insurance.webp "protect.me is an accident insurance by NN Insurance Hungary, designed with Frontìra")
_opposite-shoes-tvc-3092.webp "Director: Nemanja Novaković nDOP: Lazar Bogdanović nProducer: Aleksandar Pejčić nProduction: NN media nColor: Nikola Marinković nEditor: Marko DžambićnClient: Opposite FashionnnModel : Famous Serbian singer Nataša Bekvalac")
_2014-j-88-hull-37-available-for-sale-offered-by-karma-yacht-sales.webp "S/V")
_deep-learning-for-robotic-mass-transport-cloaking.webp "Authors: Reza Khodayi-mehr and Michael M. ZavlanosnnDescription: The contour plot on the left shows the time-dependent source field as controlled by the two mobile robots while the right contour plot depicts the corresponding time-dependent concentration field. The black square denotes the safe zone whereas the black circle and star denote the locations of the two mobile robots over time, respectively. Moreover, the dashed circle shows the pre-defined curve that constrains the paths of the robot")
_askhab.webp "Askhab from nn model")
_neural-network-solution-of-1dt-advection-diffusion-pde-high-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 high Peclet number obtained using the VarNet library. This solution corresponds to a highly advective case for which the analytical solution is unstable.nnAbstract: In this paper we propose a new model-based unsupervise")
_act26nov-b-yesha-present-3nn-model.webp "ACT26NOV-B Yesha present 3NN Model from nn model")
_protect-me-new-model-for-accident-insurance-long.webp "protect.me is an accident insurance by NN Insurance Hungary, designed with Frontìra. nAwards: IF Design Award in Service Design discipline 2019; Best New Mobile App award 2018")
_morphozoic-update-10-15-by-tom-portegys.webp "Short presentation to DevoWorm group on Morphozoic (hybrid CA/GA/NN model for pattern formation and embryogenesis)")
_silo-emmanuel-abbe.webp "Date: 2021-04-21nnTitle: Fundamental limits of (S)GD on neural networksnnAbstract: We consider the learning paradigm consisting of training general neural networks (NN) with (S)GD. What is the class of functions that can be learned with this paradigm? How does it compare to known classes such as PAC and SQ? Is depth/overapametrization needed to learn certain classes? We show that SGD on NN is equivalent to PAC while GD on NN is equivalent to SQ, obtaining a separation between the classes learned")
_viper-400-black.webp "Brand: OverdrivenModel: Viper 400nColor: Black, Red, YellownEngine: Parallel Twin CylindernDisplacement: 396ccnPower: 30hp @ 6,500 RpmnTorque: 22.5 N.n. @ 6,500 RpmnBore x Stroke: 69 x 62mmnCooling System: Liquid CoolingnCompression Ratio: 9.8:1nFuel System:")
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