Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
An extension of XGBoost to probabilistic modelling
portion, a Python library providing data structure and operations for intervals.
Evidence-aware multi-engine mathematics runtime for LLMs: exact, symbolic, formal, certified-interval and numeric computation with typed MathIR, trust labels, and full provenance
Puts back what Garmin strips from the FIT files it sends to Intervals.icu - and syncs the wellness data the official sync misses
Integer multiplication below n log n: a conditional witness kappa = 6685733/10^10 (> 2^-11) for T(n) = O(n (log n)^(1-kappa)) in the multitape model, building on OpenAI's problem and Colkitt's integer-mult-bounds: certificates, independent replays, Lean 4 checks