log-domain VS lbfgs

Compare log-domain vs lbfgs and see what are their differences.

log-domain

This package provides log-domain floats, doubles and complex numbers for Haskell. (by ekmett)

lbfgs

Haskell binding for liblbfgs (by wavewave)
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log-domain lbfgs
0 0
12 4
- -
3.0 3.7
8 months ago 10 months ago
Haskell C
GNU General Public License v3.0 or later GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

log-domain

Posts with mentions or reviews of log-domain. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning log-domain yet.
Tracking mentions began in Dec 2020.

lbfgs

Posts with mentions or reviews of lbfgs. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning lbfgs yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing log-domain and lbfgs you can also consider the following projects:

affine-invariant-ensemble-mcmc

hasty-hamiltonian - Speedy gradient-based traversal through parameter space.

compensated - Compensated floating-point arithmetic

mighty-metropolis - The classic Metropolis sampling algorithm.

roman-numerals - Parsing and pretty printing of Roman numerals

sparse-linear-algebra - Numerical computation in native Haskell

hyperloglog - A constant-memory approximation of set membership

haskell-mpfr - MPFR bindings for Haskell

repr - Render overloaded expressions to their textual representation.

lens-aeson - Traversals and Prisms for Data.Aeson

approximate - Approximate discrete values and numbers

half - half-precision floating-point