Variable expectations

Title Description Reading Time
Two roads to AI’s future Superhuman oracles and social minds 14 min
Navigating published literature with full control Tracking a field in real time, cheaply 14 min
Enabling AI in LNP engineering Virtual spaces and chemical languages 14 min
Exploring perturbation data in drug discovery Some trajectories of AI-guided exploration 5 min
Procedurally generating data for tuning technical LLMs Turning tacit technical knowledge into prediction 7 min
In silico fragment synthesis with combinatorial chemistry Revisiting LNP libraries for rational design 6 min
Combinatorial chemistry and in silico decompositions Decomposition as inverted synthesis 9 min
Embedding too many chemicals to count Discrete combinatorics as continuous embeddings 4 min
Sourcing chemical structures for in silico discovery Getting ionizable lipid structures from online catalogs 11 min
Navigating vast chemical spaces without enumeration Synthons and how to express them 7 min
Screening too many chemicals to count Searching trillions of structures on a laptop 14 min
Decomposition and synthesis with a flexible reaction set Reaction sets for different in silico ultralarge spaces 9 min
Visualizing in silico chemical decompositions Ways to view ultralarge chemical spaces 1 min
Multi-criterion optimization and decision-making Trading off many objectives in drug discovery 4 min
Making animations and gifs Stringing together plots into gifs 1 min
Color for an applied data scientist Perplexingly useful colormap tidbits 11 min
Lightweight, interactive QSAR importance plots A self-contained visualization of atomic contributions to models 6 min
Interactive browser, part 2 An interactively clustered heatmap 7 min
Building an interactive data browser Lightweight, performant exploration of chemical space 9 min
Interactive browser, part 3 - subset selection and scaling Repurposing for single-cell data 10 min
Building graphs from gene sets Gene-gene graphs and the Gene Ontology 5 min
Looking up gene sets in databases Some wrapper code for gProfiler 0 min
Random projections and dimensionality reduction Efficient, general applied tools 9 min
Tree! I am no tree! I am an embedding! Hierarchies on data 8 min
From local change to global order Calculus on graphs as manifolds 17 min
Graph sparsification Removing edges while maintaining connectivity 13 min
Localized graph descriptions Learning an interpretable coordinate system for a dataset 4 min
Detecting motifs in networks Some linear algebra one-liners 4 min
Generating samples from kNN graphs For “stationary” signals 5 min
Graph-based semi-supervised prediction Harmonic analysis for learning on graphs 8 min
Constructing data-driven neighborhood graphs Building neighborhood graphs from datasets 12 min
Probability densities on embeddings Tools for modeling distributions on data neighborhoods 8 min
SVD-based imputation methods Using the SVD to perform ultra-efficient imputation 1 min
Laplacian regularization and trend filtering Using graphs to regularize learning 8 min
Measuring association between variables A few new coefficients 12 min
The SVD and friends Breaking down a (sparse) matrix quickly 11 min
Foundations of concentration and entropy Where entropy comes from 10 min
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