JakobRobnik/MicroCanonicalHMC
MCHMC: sampler from an arbitrary differentiable distribution
Jupyter NotebookGPL-3.0
Stargazers
- 2019mohamedProteinea
- aboucaudLaboratoire APC, CNRS/IN2P3
- AFg6K7h4fhy2
- aymgal
- b-remyPrinceton, @astro-data-lab
- conorhassanQueensland University of Technology
- davidnabergojUniversity of Ljubljana, Faculty of Computer and Information Science
- dehorsleyHobart, Tasmania
- didsorita
- DPS0340@MondrianAI @SW-Maestro-OSS
- dylanhmorrisCenter for Forecasting and Outbreak Analytics, US Centers for Disease Control and Prevention
- edong6768POSTECH
- emaballarinDept. of Maths, UniTS | @LACoNIC-UniTS ⊆ @ailab-units | @sissa-data-science | @AI-Student-Society
- HajimeKawaharaJAXA/ISAS
- jacob-hjortlund
- jcblemaiUniversity of North Carolina at Chapel Hill
- jmsullMIT
- johnveitchUniversity of Glasgow
- kazewong
- kleinhenzLawrence Berkeley National Laboratory
- malbergo
- Maverick-OhMerced, California, USA
- mj-willUniversity of Portsmouth
- mwalmsleyUniversity of Toronto, @zooniverse
- pierreglaserUCL
- PJRoome
- pthouvenin
- RaunakDeyUniversity of Maryland, Georgia Tech.
- RichardGrumitt
- rkarur
- rok-cesnovarCerknica, Slovenia
- seabbs@epinowcast @EpiAware @epiforecasts
- sjbeckettUniversity of Maryland
- williwilliams3
- WuShichaoMax Planck Institute for Gravitational Physics
- zxj-git