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gabrieldernbach/README.md

๐Ÿ‘‹ Hi, Iโ€™m Gabriel Dernbach

Website

Welcome to my GitHub profile!
I work on machine learning, foundation models, and causal inference โ€” often with applications in computational pathology and single-cell biology.

๐Ÿ”— Explore my personal site for:

  • Research portfolio
  • Publications and preprints
  • Projects and datasets
  • Notes and blog posts

๐Ÿ”ง Pinned Projects

๐Ÿ‘‰ Make sure to check my pinned repositories below for key projects.


๐Ÿ“ซ Connect

Pinned Loading

  1. python method chaining without monads python method chaining without monads
    1
    import functools
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    from joblib import Parallel, delayed
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    def compose2(f, g):
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        return lambda x: g(f(x))
  2. mine.py mine.py
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    class MINE(nn.Module):
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        """
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        Stub to implement Mutual Information Neural Estimation.
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        See https://arxiv.org/pdf/1801.04062
  3. Solving mnist, fast and short Solving mnist, fast and short
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    from torchvision.datasets import MNIST
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    import numpy as np
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    def data(train):
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        mnist = MNIST(root='.', download=True, train=train)
  4. leverage_scores.py leverage_scores.py
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    # leverage scores l_[i] = tr(X @ (X^T X)^-1 @ X)
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    # indication of self-sensitivity or self-influence of i-th sample.
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    import numpy as np
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    n = 2048 # samples
  5. approximate_joint_diagonalization approximate_joint_diagonalization Public

    parallel joint diagonlization

    Python 7 3