This appendix collects assorted references and curiosities that pair well with this course. Items are grouped by theme; brief annotations indicate how you might use each link. Some links may require institutional access or sign-in.
Probability, Geometry, and Visualization¶
- Buffon’s Needle (Monte Carlo demo): Short post with code and derivation; nice for geometric probability and basic MC error analysis.
https://simonensemble .github .io /posts /2018 -04 -11 -buffon/ - Gallery of Curves: Visual encyclopedia of classic planar curves; quick inspiration for parametric plotting.
Gallery of curves - Differential Geometry of Surfaces (Wikipedia): Definitions and formulas you can consult when working with meshes and curvature.
Differential geometry of surfaces - Why do golf balls have dimples? (COMSOL blog): Boundary layer, drag, and turbulence primer; good for discussion on modeling limits.
https://www .comsol .com /blogs /why -do -golf -balls -have -dimples
Statistical Learning, Surrogates, and Bayesian Modeling¶
- Supervised Machine Learning for Science (open book): Science-oriented ML text with examples; good companion reading.
https://ml -science -book .com/ - Surrogates: Gaussian Process Modeling, Design, and Optimization: Reference on GP modeling and design of experiments. (N. G. Gramacy, Routledge, 2020).
https://www .routledge .com /Surrogates -Gaussian -Process -Modeling -Design -and -Optimization -for -the /Gramacy /p /book /9780367415426 - Stan Reference Manual: Canonical documentation for probabilistic modeling and inference.
https://mc -stan .org /docs /reference -manual /index .html - Understanding Deep Learning (open book): Rigorous DL text that complements our ML units.
https://udlbook .github .io /udlbook/
Symbolic Regression and Scientific ML¶
- SymbolicRegression.jl (Stable docs): Tools for fitting closed-form expressions to data (Julia).
https://ai .damtp .cam .ac .uk /symbolicregression /dev/ - SciCode-Bench: Benchmark for scientific code generation; context for LLMs that write science code.
https://scicode -bench .github .io/ - How chaotic is chaos?: Perspective on over-claiming accuracy for chaotic systems; useful for limits-of-prediction discussion.
https://www .stochasticlifestyle .com /how -chaotic -is -chaos -how -some -ai -for -science -sciml -papers -are -overstating -accuracy -claims/
Molecules, Materials, and Structure Prediction¶
- MolCalc: Browser-based molecule builder with quick property estimates; lightweight for ideas and sanity checks.
https://molcalc .org/ - AlphaFold Protein Structure Database (EBI): Canonical database for predicted structures.
https://alphafold .ebi .ac .uk/ - AlphaFold server (3rd-party interface): Convenience interface; not the canonical EBI database.
https://alphafoldserver .com /about - DeepMind blog: Millions of new materials discovered with deep learning: Overview and pointers for GNoME-style materials discovery.
https://deepmind .google /discover /blog /millions -of -new -materials -discovered -with -deep -learning/ - Microsoft Research: AI meets materials discovery: Feature on AI-accelerated pipelines (e.g., MatterSim/MatterGen).
https://www .microsoft .com /en -us /research /story /ai -meets -materials -discovery/
Geometry, Proof Automation, and “AI doing math”¶
- AlphaGeometry: Olympiad-level geometry solving; framing for automated theorem proving.
https://deepmind .google /discover /blog /alphageometry -an -olympiad -level -ai -system -for -geometry/ - AI solves IMO problems at silver-medal level: Broader context on problem-solving systems.
https://deepmind .google /discover /blog /ai -solves -imo -problems -at -silver -medal -level/
Notable papers and commentary (with DOIs where available)¶
- Unbiasing fermionic quantum Monte Carlo with a quantum computer. Nature 603, 416–420 (2022). DOI: 10.1038/s41586-021-04351-z.
https://www .nature .com /articles /s41586 -021 -04351-z - “ChatGPT is bullshit.” Ethics and Information Technology 26, 38 (2024). DOI: 10.1007/s10676-024-09775-5.
Hicks et al. (2024) - Computing hydration free energies of small molecules with first-principles accuracy. arXiv (2024–2025). DOI: 10.48550/arXiv.2405.18171. (See highlight: “Computing solvation free energies…”, Comp. Chem. Highlights, July 2025.)
https://arxiv .org /abs /2405 .18171
http://www .compchemhighlights .org /2025 /07 /computing -solvation -free -energies -of .html ?m =1
AI for Teaching and Policy (instructor resources)¶
- Generative AI Teaching Activities (WUSTL CTL): Vetted classroom activities and assignments.
https://ctl .wustl .edu /resources /generative -ai -teaching -activities -online -repository/ - Teaching Naked (prompts & compendium): Ready-to-use prompts/handouts for course design.
https://teachingnaked .com /prompts/
Numerical Computing, Style, and Supplemental Texts¶
- Fundamentals of Numerical Computation (Julia): Modern numerics text with worked examples.
https://tobydriscoll .net /fnc -julia /home .html - PEP 8 — A foolish consistency is the hobgoblin of little minds: Style guidance and when to deviate pragmatically.
https://peps .python .org /pep -0008 / #a -foolish -consistency -is -the -hobgoblin -of -little -minds - A practical introduction to LLMs in Python (ebook/notes): Applied overview; useful for quick prototypes.
https://pointbreezepubs .gumroad .com /l /llm
Media, Playlists, and Miscellany¶
- MIT 8.334 Statistical Mechanics II (playlist): Advanced stat-mech enrichment.
https://www .youtube .com /playlist ?list = PLUl4u3cNGP63HkEHvYaNJiO0UCUmY0Ts7 - YouTube short — materials/heat-treating clip (quick curiosity).
https://www .youtube .com /shorts /W2xxT3b -4H0 - YouTube short — science explainer (quick curiosity).
https://www .youtube .com /shorts /Wc7Q2UJ3WtE - General-audience coverage: NYT — “AI Test: Humanity’s Last Exam” (Jan 23, 2025). Paywalled.
https://www .nytimes .com /2025 /01 /23 /technology /ai -test -humanitys -last -exam .html - Google Research — Imagen: Text-to-image diffusion models (for visualization discussions).
https://imagen .research .google/
Course-adjacent and access-limited items¶
- LinkedIn post (Justin Hodges): Access and visibility may vary.
https://www .linkedin .com /posts /justin -hodges -phd -3432a58b _physics -statistics -math -ugcPost -7293143917791694848 -3fxk/ - Cornell Chem 7870 homework: Reference assignment on PDE solvers; content may change.
https://github .com /cornell -chem -7870 /chem -7870 -2025 -pde -solvers -homework _10 - LinkedIn post (Andrew Rosen): Access and visibility may vary.
https://www .linkedin .com /posts /andrew -s -rosen _while -im -a -big -proponent -of -general -purpose -activity -7359219267877130242 -2Zeb / ?rcm = ACoAAATbG _QBvs2odhZQvbGP20f5rd _uxTwal8c
Notes¶
- Links are intentionally eclectic; use them for inspiration, enrichment, and discussion.
- If you notice a dead link, please open an issue or PR in the course repository: https://
github .com /wexlergroup /comp -prob -solv.
- Hicks, M. T., Humphries, J., & Slater, J. (2024). ChatGPT is bullshit. Ethics and Information Technology, 26(2). 10.1007/s10676-024-09775-5