Adding Metropolis-Adjusted Langevin Algorithm

[arrjon]

This pull request introduces a new gradient-based sampler, the Metropolis-Adjusted Langevin Algorithm (MALA), to the pypesto.sample module, and refactors the covariance regularization in the adaptive Metropolis sampler. The changes also enhance the test suite and documentation to demonstrate and validate the new functionality.

I refactored the covariance regularization to return both the Cholesky decomposition and the regularized covariance matrix, improving numerical stability. The regularization function now supports multiple attempts and safe fallback strategies. Before it could happen that adaptive MCMC just fails at some point due to an ill-conditioned proposal covariance.

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Codecov Report

❌ Patch coverage is 92.13483% with 7 lines in your changes missing coverage. Please review.
✅ Project coverage is 84.36%. Comparing base (bc7d89a) to head (7cad7fd).

Files with missing lines	Patch %	Lines
pypesto/sample/adaptive_metropolis.py	87.87%	4 Missing ⚠️
pypesto/sample/mala.py	93.18%	3 Missing ⚠️
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Additional details and impacted files

@@             Coverage Diff             @@
##           develop    #1617      +/-   ##
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- Coverage    84.37%   84.36%   -0.01%     
===========================================
  Files          164      165       +1     
  Lines        14320    14395      +75     
===========================================
+ Hits         12082    12145      +63     
- Misses        2238     2250      +12     

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[PaulJonasJost]

Awesome, looks good to me, thanks :)

[arrjon]

@dilpath, this is ready to merge I think