Machine Learning

Predicting Gene Expression From Sequence
In this post, I cover the most recent deep learning approaches to predicting gene expression from DNA sequence.
May 20, 2025 11 min read Machine Learning, Computational Biology, Bioinformatics
Predicting Gene Expression From Sequence
A Machine Learning Researcher's Guide to Multiomics Analysis
This post introduces the concept of multiomics analysis, its significance in modern bioinformatics, and the challenges it presents for machine learning researchers.
May 17, 2025 9 min read Machine Learning, Computational Biology, Bioinformatics
A Machine Learning Researcher's Guide to Multiomics Analysis
Product Manifold Representations for Learning on Biological Pathways
Machine learning models that embed graphs in non-Euclidean spaces have shown substantial benefits in a variety of contexts, but their …
Daniel McNeela, Frederic Sala, Anthony Gitter
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Product Manifold Representations for Learning on Biological Pathways
GROG - Reducing LLM Hallucinations for Improved Legal Reasoning
In this work we introduce Graph Retrieval-Optimized Generation (GROG), a method for reducing LLM hallucinations in contexts where …
Daniel McNeela
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GROG - Reducing LLM Hallucinations for Improved Legal Reasoning
Almost Equivariance via Lie Algebra Convolutions
Recently, the equivariance of models with respect to a group action has become an important topic of research in machine learning. …
Daniel McNeela
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Almost Equivariance via Lie Algebra Convolutions