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mlx-code is a Python package that provides a local-first LLM coding agent for Apple Silicon, bundling an MLX inference server, multi-protocol API support, git worktree isolation, and composable multi-agent primitives.
This paper presents FederatedRSF, a Python package for federated random survival forests that handles partially overlapping medical data across institutions without sharing raw data, and demonstrates comparable performance to centralized training on breast cancer data.
A 16-year-old developer created sage-explainer, a Python package that approximates prediction sensitivity to features for black-box models like random forests and XGBoost, offering more stable results than centered finite differences.
bde is a Python package that brings sampling-based Bayesian Deep Learning to practitioners via the MILE method, combining JAX's speed with scikit-learn's API for tabular supervised learning tasks.