Topic: sde Goto Github
Some thing interesting about sde
Some thing interesting about sde
sde,Python package used for generating HTML reports about the contents of Esri geodatabases.
User: alexarcpy
sde,Diffusion Models in Medical Imaging (Published in Medical Image Analysis Journal)
User: amirhossein-kz
Home Page: https://www.sciencedirect.com/science/article/pii/S1361841523001068
sde,Predicting stock prices using Geometric Brownian Motion and the Monte Carlo method
User: bottama
sde,A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining, ICML'23
User: chao1224
Home Page: https://chao1224.github.io/MoleculeSDE
sde,A collection of a number of design patterns and principles written in Kotlin
User: devansh-maurya
Home Page: https://devansh233.gitbook.io/design-patterns-and-principles/
sde,A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
Organization: dlr-rm
Home Page: https://rl-baselines3-zoo.readthedocs.io
sde,PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Organization: dlr-rm
Home Page: https://stable-baselines3.readthedocs.io
sde,Matlab Toolbox for the Numerical Solution of Stochastic Differential Equations
User: horchler
Home Page: http://biorobots.case.edu
sde,A collection of C/C++ programs and Python scripts to be used in conjunction with Intel Software Development Emulator (Intel SDE, available externally separately). The purpose is to use record/replay functionality in SDE for program analysis.
Organization: intel
sde,Computing FLOPs with Intel Software Development Emulator (Intel SDE)
Organization: it4innovations
sde,An R Package for Monte Carlo Option Pricing Algorithm for Jump Diffusion Models with Correlational Companies
User: jirotubuyaki
sde,Maximum Likelihood estimation and Simulation for Stochastic Differential Equations (Diffusions)
User: jkirkby3
sde,This repository contains opportunities for you to apply to more than 400 product base companies(NOT JUST FAANGM) & good start-ups.
User: kaustubh-natuskar
Home Page: https://kaustubh-natuskar.github.io/moreThanFAANGM/
sde,The Repository Contains All the Technical Stuff's Related To SDE
User: mrpawan-gupta
sde,A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.
User: mschauer
sde,A collection of awesome framework, libraries, learning tutorials, videos, webcasts, technical resources and cool stuff about Interview for Security & Computer Engineering.
User: paulveillard
sde,Solving linear, nonlinear equations, ordinary differential equations, ... using numerical methods in fortran
User: planelles20
sde,Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
Organization: sciml
Home Page: https://docs.sciml.ai/Catalyst/stable/
sde,The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
Organization: sciml
sde,Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning
Organization: sciml
Home Page: https://docs.sciml.ai/DiffEqBayes/stable/
sde,A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
Organization: sciml
Home Page: https://docs.sciml.ai/DiffEqCallbacks/stable/
sde,Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)
Organization: sciml
Home Page: https://benchmarks.sciml.ai/
sde,Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
Organization: sciml
Home Page: https://docs.sciml.ai/DiffEqDocs/stable/
sde,Differential equation problem specifications and scientific machine learning for common financial models
Organization: sciml
sde,GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
Organization: sciml
Home Page: https://docs.sciml.ai/DiffEqGPU/stable/
sde,A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)
Organization: sciml
Home Page: https://docs.sciml.ai/DiffEqNoiseProcess/stable/
sde,Linear operators for discretizations of differential equations and scientific machine learning (SciML)
Organization: sciml
Home Page: https://docs.sciml.ai/DiffEqOperators/stable/
sde,Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
Organization: sciml
Home Page: https://docs.sciml.ai/DiffEqParamEstim/stable/
sde,A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools
Organization: sciml
sde,Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
Organization: sciml
sde,Solving differential equations in R using DifferentialEquations.jl and the SciML Scientific Machine Learning ecosystem
Organization: sciml
sde,Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
Organization: sciml
Home Page: https://docs.sciml.ai/DiffEqDocs/stable/
sde,Build and simulate jump equations like Gillespie simulations and jump diffusions with constant and state-dependent rates and mix with differential equations and scientific machine learning (SciML)
Organization: sciml
Home Page: https://docs.sciml.ai/JumpProcesses/stable/
sde,An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
Organization: sciml
Home Page: https://mtk.sciml.ai/dev/
sde,A standard library of components to model the world and beyond
Organization: sciml
Home Page: https://docs.sciml.ai/ModelingToolkitStandardLibrary/stable/
sde,A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations
Organization: sciml
Home Page: https://docs.sciml.ai/MultiScaleArrays/stable/
sde,The SciML Scientific Machine Learning Software Organization Website
Organization: sciml
Home Page: https://sciml.ai/
sde,The Base interface of the SciML ecosystem
Organization: sciml
Home Page: https://docs.sciml.ai/SciMLBase/stable
sde,Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
Organization: sciml
Home Page: https://docs.sciml.ai/SciMLBenchmarksOutput/stable/
sde,A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
Organization: sciml
Home Page: https://docs.sciml.ai/SciMLSensitivity/stable/
sde,Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
Organization: sciml
Home Page: https://tutorials.sciml.ai
sde,Workshop materials for training in scientific computing and scientific machine learning
Organization: sciml
Home Page: https://docs.sciml.ai/SciMLWorkshop/stable/
sde,Solvers for steady states in scientific machine learning (SciML)
Organization: sciml
sde,Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
Organization: sciml
sde,Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code
Organization: stable-baselines-team
Home Page: https://sb3-contrib.readthedocs.io
sde,Python package to discover stochastic differential equations from time series data
Organization: tee-lab
sde,New home of Swift Development Environment for VS Code
User: vknabel
Home Page: https://marketplace.visualstudio.com/items?itemName=vknabel.vscode-swift-development-environment
sde,公众号【码农田小齐】的分类合集
User: xiaoqi6666
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