@@ -29,11 +29,11 @@ sampling are completely customizable.

 The following learners are implemented:

-* `Learner1D`, for 1D functions `f: ℝ → ℝ^N`

-* `Learner2D`, for 2D functions `f: ℝ^2 → ℝ^N`

-* `AverageLearner`, For stochastic functions where you want to average the result over many evaluations

-* `IntegratorLearner`, for when you want to intergrate a 1D function `f: ℝ → ℝ`

-* `BalancingLearner`, for when you want to run several learners at once, selecting the "best" one each time you get more points

+* `Learner1D`, for 1D functions `f: ℝ → ℝ^N`,

+* `Learner2D`, for 2D functions `f: ℝ^2 → ℝ^N`,

+* `AverageLearner`, For stochastic functions where you want to average the result over many evaluations,

+* `IntegratorLearner`, for when you want to intergrate a 1D function `f: ℝ → ℝ`,

+* `BalancingLearner`, for when you want to run several learners at once, selecting the "best" one each time you get more points.

 In addition to the learners, `adaptive` also provides primitives for running

 the sampling across several cores and even several machines, with built-in support

@@ -64,8 +64,8 @@ in the repository.

 ## Credits

 We would like to give credits to the following people:

 - Pedro Gonnet for his implementation of [`CQUAD`](https://www.gnu.org/software/gsl/manual/html_node/CQUAD-doubly_002dadaptive-integration.html), "Algorithm 4" as described in "Increasing the Reliability of Adaptive Quadrature Using Explicit Interpolants", P. Gonnet, ACM Transactions on Mathematical Software, 37 (3), art. no. 26, 2010.

-- Christoph Groth for his Python implementation of [`CQUAD`](https://gitlab.kwant-project.org/cwg/python-cquad) which served as basis for the [`IntegratorLearner`](adaptive/learner/integrator_learner.py)

-- Pauli Virtanen for his `AdaptiveTriSampling` script (no longer available online since SciPy Central went down) which served as inspiration for the [`Learner2D`](adaptive/learner/learner2D.py)

+- Christoph Groth for his Python implementation of [`CQUAD`](https://gitlab.kwant-project.org/cwg/python-cquad) which served as basis for the [`IntegratorLearner`](adaptive/learner/integrator_learner.py).

+- Pauli Virtanen for his `AdaptiveTriSampling` script (no longer available online since SciPy Central went down) which served as inspiration for the [`Learner2D`](adaptive/learner/learner2D.py).

 For general discussion, we have a [chat channel](https://chat.quantumtinkerer.tudelft.nl/external/channels/adaptive). If you find any bugs or have any feature suggestions please file a GitLab [issue](https://gitlab.kwant-project.org/qt/adaptive/issues/new?issue) or submit a [merge request](https://gitlab.kwant-project.org/qt/adaptive/merge_requests).