Variable expectations

Title Description Reading Time
Navigating published literature with full control Tracking a field in real time, cheaply 14 min
Procedurally generating data for tuning technical LLMs Turning tacit technical knowledge into prediction 8 min
AI in the small-molecule discovery funnel Virtual spaces and chemical languages 14 min
Linear algebra in the AI world Same classics, new applications 4 min
In silico fragment synthesis with combinatorial chemistry Revisiting LNP libraries for rational design 7 min
Combinatorial chemistry and in silico decompositions Decomposition as inverted synthesis 10 min
Searching too many chemicals to count Searching trillions of structures on a laptop 7 min
Embedding ultralarge spaces Revisiting LNP libraries for rational design 2 min
Sourcing chemical structures for in silico discovery Getting ionizable lipid structures from online catalogs 10 min
Screening too many chemicals to count Searching trillions of structures on a laptop 15 min
Decomposition and synthesis with a flexible reaction set Reaction sets for different in silico ultralarge spaces 10 min
Making animations and GIFs Stringing together plots into GIFs 2 min
Color for an applied data scientist Embarrassingly useful colormap tidbits 12 min
Building an interactive data browser Lightweight, performant exploration of chemical space 10 min
Graphs as interactive diagrams Translating between interactive flowcharts and data science 8 min
Two roads to AI’s future Superhuman oracles and social intelligences 15 min
Some useful hashing tricks Indexing for numbering and obfuscation 5 min
Visualization tools for science and computation Increasing capabilities in domain-specific languages 7 min
Lightweight, interactive QSAR importance plots A self-contained visualization of atomic contributions to models 7 min
Interactive browser, part 2 - finding and displaying structure An interactively clustered heatmap 8 min
Visualizing in silico chemical decompositions Ways to view ultralarge chemical spaces 2 min
Interactive browser, part 3 - subset selection and scaling Repurposing for single-cell data 11 min
Looking up gene function in databases Cross-referencing many databases at once 19 min
Gene sets from gene function Deriving gene sets to steer genomic learning 15 min
Exploring perturbation data in drug discovery Some trajectories of AI-guided exploration 5 min
Tree! I am no tree! I am an embedding! Hierarchies on data 8 min
Graph sparsification Removing edges while maintaining connectivity 13 min
Localized graph descriptions Learning an interpretable coordinate system for a dataset 5 min
Laplacian regularization and trend filtering Using graphs to regularize learning 9 min
Graph-based semi-supervised prediction Harmonic analysis for learning on graphs 8 min
Using graphs to express structure Efficient, practical tools 1 min
Calculus on graphs as manifolds From local change to global order 15 min
Detecting motifs in networks Some linear algebra one-liners 13 min
Global evaluations from two-way comparisons Quickly learning from pairwise feedback 10 min
Generating signals from neighborhood graphs Using graphs as compressed representations 6 min
How to construct graphs for data analysis Building neighborhood graphs from datasets 13 min
Low-rank approximation of matrices and graphs Efficient, robust, simple, and interpretable 4 min
The SVD and friends Breaking down a (sparse) matrix quickly 12 min
Random projections and dimensionality reduction Efficient, general applied tools 10 min
Solving sparse linear equations Logging the results of Gaussian elimination 16 min
SVD-based imputation methods Using the SVD to perform ultra-efficient imputation 2 min
Probability densities on embeddings Modeling distributions on data neighborhoods 8 min
Which data are intrinsically hard to classify? Margins for classifier embeddings 13 min
Evaluating extremely imbalanced classification Finding needles in a haystack 14 min
Measuring association between variables A few new coefficients 12 min
Multi-criterion optimization and decision-making The power of weighted sums 13 min
Foundations of concentration and entropy Where entropy comes from 7 min
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