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create my best developement environment
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License: No License (No License)Registration aims to decompose amplitude and phase variation of samples of curves. Phase variation is captured by warping functions which monotonically trans- form the domains. Resulting registered curves should then only exhibit amplitude variation. Most existing methods assume that all sample functions exhibit a typical sequence of shape features like peaks or valleys, and registration focuses on aligning these features. In this paper we adopt a more general point of view which goes be- yond feature alignment. We present a registration method where warping functions are defined in such a way that the resulting registered curves span a low dimensional linear function space. The approach may be used as a tool for analyzing any type of functional data satisfying a structural regularity condition called “bounded shape variation”. Problems of identifiability are discussed in detail, and connections to es- tablished registration procedures are analyzed. The method is applied to real and simulated data.
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kudaby ununhexium
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proc-modulesby pop-os
Rust crate for fetching a list of kernel modules from /proc/modules
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LightORamaby rmbolger
Scripts and code relating to Light-O-Rama based light shows
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gfx_kissby kvark
[DEPRECATED] Simple drawing API for gfx-rs
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Acer_Fan_Controllerby CristianSarac
UI Application for controlling the speed of the fans for Acer laptops
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cudavecby unixpickle
CUDA plugin for anyvec, done right.
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2by mumax
mumax2 GPU-accelerated micromagnetics
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Xavier_NXby zinuok
setting guides about Nvidia Xavier NX (camera, third party program like teamviewer)
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tornadovm-installerby beehive-lab
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slurm_ddpby krokodilno
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kubernetes-gpuby voor
Adding GPU support to Cluster API with base image modifications
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nvidia-device-pluginby cicdteam
kops hook for NVIDIA GPU Driver and DevicePlugin Installation
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jetson_nvidia_dockersby Tony607
Jetson nvidia dockers
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NV-Cardby YiPrograms
A script to switch NVIDIA graphics card using bbswitch/kernel PM
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Carme-Docuby CarmeTeam
Documentation Project for Carme
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nvidia-cudaby archerslaw
nvidia cuda and driver automatically install with cloud-init user-data
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CUDA-OpenCVby jarleven
Automatic install script for OpenCV CUDA GPU Linux Ubuntu 16.04
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nvidiaby TechnologyClassroom
Wrapper scripts to install proprietary NVIDIA drivers on GNU/Linux systems
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dti_preprocessby RIKEN-BCIL
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exacloud_tutorialby laderast
Updated tutorial on using exacloud and slurm. Start here: https://laderast.github.io/exacloud_tutorial
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dokku-mlby RagingTiger
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dev_env_dockerby kakibara
create my best developement environment
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nvidia_driver_docker_volumeby djx339
Using NVIDIA GPU inside the docker container.
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nvidia-375.39-patch-linux-4.10by aniljava
Nvidia driver patch for 4.10 kernel, Ubuntu Zesty Zapus, 17.04
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ubuntu_preempt_rtby chopyy
Enable real-time capabilities of the Ubuntu Linux kernel.
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cudaby k8sp
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bfarmxby rfabbri
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clouddocsby sara-nl
HPC Cloud documentation
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SuperPascalby Classic-Tools
SuperPascal compiler and virtual machine interpreter developed by Per Brinch Hansen (1993)
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docker-boinc-gpuby ozzyjohnson
A container with all the necessary to BOINC GPU projects via CUDA within Docker.
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CLgrepby NZDIS
Parallel pattern matching implementation in OpenCL.
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blazemap-coreby patrimart
A blazing fast heatmap library. GPU-accelerated by GPU.js. Written in TypeScript.
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elm-media-primitivesby danabrams
A set of media API primitives that require kernel code.
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LauraeCppby Laurae2
Parallel R for HPC on a Single Computer using C++
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Nonparametric-Registration-to-Low-Dimensional-Function-Spacesby heikowagner
Registration aims to decompose amplitude and phase variation of samples of curves. Phase variation is captured by warping functions which monotonically trans- form the domains. Resulting registered curves should then only exhibit amplitude variation. Most existing methods assume that all sample functions exhibit a typical sequence of shape features like peaks or valleys, and registration focuses on aligning these features. In this paper we adopt a more general point of view which goes be- yond feature alignment. We present a registration method where warping functions are defined in such a way that the resulting registered curves span a low dimensional linear function space. The approach may be used as a tool for analyzing any type of functional data satisfying a structural regularity condition called “bounded shape variation”. Problems of identifiability are discussed in detail, and connections to es- tablished registration procedures are analyzed. The method is applied to real and simulated data.
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R-Causal-Inferenceby benhhu
R codes for PHC6016 Causal Inference Lecture
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RCUDAby yuanli22
R GPU computing package by Nvidia's CUDA
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EpiModelHPCby statnet
High-Performance Computing Extensions for EpiModel
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gpuClassifieRby IshmaelBelghazi
CUDA and C linear classifier for R
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team-iosby caneroj1
This is the repository for the CSC470 iOS Cloud Computing Project.
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3Cnetby KyoungYeulLee
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p3aby SNLComputation
Portably Performant Physical Algebra
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FlexRIO-P2P-GPUby JohnnyGOX17
POC for utilizing peer-to-peer data streams between a National Instruments FlexRIO device and a NVIDIA GPU
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NexusMinerby Nexusoft
Nexus Miner for Hash channel with FPGA/GPU/CPU pool and solo.
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