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https://github.com/axsk/augmented-jump-chain

Continuation of AJC work (2020-21) with trips to hitting time optimization, spa, sqra, isokann, committor neural network, sparse boxes, voronoi linear program, meta sgd, adaptive euler maruyama

https://github.com/axsk/augmented-jump-chain

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ○
    Academic publication links
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (4.5%) to scientific vocabulary

Keywords

ajc committor isokann julia neural-network optimization paper python scrapbook sqra zib
Last synced: 5 months ago · JSON representation

Repository

Continuation of AJC work (2020-21) with trips to hitting time optimization, spa, sqra, isokann, committor neural network, sparse boxes, voronoi linear program, meta sgd, adaptive euler maruyama

Basic Info
  • Host: GitHub
  • Owner: axsk
  • Language: Jupyter Notebook
  • Default Branch: master
  • Homepage:
  • Size: 15.4 MB
Statistics
  • Stars: 0
  • Watchers: 3
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
ajc committor isokann julia neural-network optimization paper python scrapbook sqra zib
Created over 5 years ago · Last pushed over 2 years ago
Metadata Files
Readme

README.md

augmented-jump-chain (former name birthdeath)

Amongst the rest, most prominently features the code for the The Augmented Jump Chain (see src/ajcs.py)

Contents

Part 1 (python)

  • EAMC + Paper Plots
  • Hitting times + Optimization (ADAM, RProp, Momentum, RMSProp)
  • Adjoint ODE solver as in SUNDIALS (for optimization of hitting times?)
  • Temporal Gillespie
  • SPA
  • SQRA (ndtorus, perturbation, derivatives for the adjoint problem)

Part 2 (julia) (most is now in Sqra.jl)

  • ISOKANN experiments
  • Committor neural network
  • Autodiff Bug MWEs
  • SparseBoxes, Sqra, picking
  • voronoi neighborhood by linear program of H. Lie
  • meta SGD
  • adaptive euler maruyama

History

WIP from 07.20 to 06.21

Continuation of https://github.com/axsk/generators and in a similar dirty state Most usefull ideas where ported to ttps://github.com/axsk/Sqra.jl

Owner

  • Name: Alexander
  • Login: axsk
  • Kind: user
  • Location: Berlin
  • Company: Zuse Institute Berlin

Mathematician

GitHub Events

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Last Year

Committers

Last synced: 8 months ago

All Time
  • Total Commits: 109
  • Total Committers: 2
  • Avg Commits per committer: 54.5
  • Development Distribution Score (DDS): 0.018
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
axsk s****3@g****m 107
Sikorski s****i@z****e 2
Committer Domains (Top 20 + Academic)
zib.de: 1

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Last synced: 8 months ago

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  • Total pull requests: 0
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  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
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  • Bot pull requests: 0
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