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The article argues that modern science is synonymous with open source software, emphasizing the need for reproducibility and the scientific method in computational research.
The paper introduces ePID, a scalable pipeline using supervised embeddings to compute partial information decomposition for symptom networks, enabling the separation of redundant and synergistic information in mental health data.
Explorations in Monte Carlo Methods is a hands-on textbook that teaches Monte Carlo methods through realistic problems and programming exercises, suitable for students in engineering, sciences, and mathematics.
The author discusses the concept of conviviality from Ivan Illich's 'Tools for Conviviality' and applies it to computational science, arguing that digital tools in research lack conviviality compared to pre-digital tools, which poses epistemic risks.
Introduces in-span learning, a method to adapt reduced-order models by streaming the model's own predictions through an incremental singular-value decomposition, reweighting and realigning the basis without changing the subspace. The approach is demonstrated on several dynamical systems and proposed as a computational-science analogue of in-context learning.
Science Superpowers is an open-source computational-science methodology for AI research agents, enforcing pre-registration and reproducible workflows to prevent p-hacking and HARKing.
SCICONVBENCH is a benchmark that evaluates LLMs on multi-turn clarification for ill-posed scientific queries across computational science domains, finding that even frontier models struggle with disambiguation and frequently make silent assumptions.