Results for “hierarchical-models”
19 skills
lingxling pymc
Build, fit, validate, and compare Bayesian models using PyMC, including hierarchical models, MCMC sampling, variational inference, posterior predictive checks, and model comparison.
253 · bundle
k-dense-ai pymc
Build, fit, validate, and compare Bayesian models using PyMC's modern API, including hierarchical models, MCMC sampling, variational inference, posterior predictive checks, and model comparison.
30.2k · bundle
alterlab-ieu alterlab-pymc
Bayesian modeling and probabilistic programming with PyMC — hierarchical models, MCMC (NUTS) sampling, variational inference, LOO/WAIC model comparison, and posterior predictive checks. Use when fitting Bayesian or hierarchical models, estimating posteriors and credible intervals, running probabilistic inference, or comparing models with LOO/WAIC. Part of the AlterLab Academic Skills suite.
60 · bundle
More results
levalencia pymc
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
3 · bundle
mesteriis threat-model
Models threats for a service, feature, endpoint, integration, or architecture: assets, attackers, boundaries, flows, and abuse cases.
0 · bundle
jrennie99-glitch hive-mind
Byzantine fault-tolerant consensus and distributed coordination. Queen-led hierarchical swarm management with multiple consensus strategies. Use when: distributed coordination, fault-tolerant operations, multi-agent consensus, collective decision making. Skip when: single-agent tasks, simple operations, local-only work.
0
akillness heretic
Runs directional ablation and refusal-direction analysis for open-weight models the user may modify; use to reduce benign over-refusal or measure refusal/KL trade-offs, not for training.
42 · bundle
projectious-work model-recommender
Recommend the right AI model for a task by scoring candidates across six dimensions (Reasoning, Engineering, Speed, Breadth, Reliability, Governance) and displaying a spider-chart profile.
0 · bundle
timlai666 pymc-bayesian-modeling
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
1 · bundle
dvy1987 model-selection
Plan which model tier handles which work BEFORE execution begins — a high-cognition model deeply understands the problem, lays the foundations, then emits a modular plan assigning each module the cheapest tier that can safely execute it, with escalation tripwires and one-way-door protection. Advisory only: it announces "next module → tier X / model Y" at each boundary and the HUMAN switches models — harnesses like Cursor cannot switch mid-run. Load when the user asks which model to use, wants a model plan, model tiers, model-tier routing, assign models to tasks or modules, says "cheap model got stuck", "which model for this task", "cost-efficient model choice", or when implementation-plan / problem-to-plan need a model: tier column. NOT dynamic-routing (plan-path selection after failure) — this skill assigns cognition tiers to work.
3 · bundle
leandrobenjaminl senior-orchestrator
Orquesta el ecosistema de agentes: decide qué modelo o tier usar, delega tareas a sub-agentes especializados y planifica arquitectura técnica.
0
snoodleboot-io feature-engineering
Cardinality and model family jointly determine the encoding.
2
snoodleboot-io model-interpretability
"Make it interpretable" is four different requests.
2
jiachen-t-wang trak-attributing-model-behavior-at-scale-arxiv-2303-14186v2
TRAK: Attributing Model Behavior at Scale
6
metinduraktr-44 pymc-bayesian-modeling
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
0 · bundle
herdiansah postgresql-table-design
Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features
23
curiositech bdi-soft-systems
Integration of BDI agent architecture with soft systems methodology for complex organizational problem-solving
10 · bundle
muratcankoylan multi-agent-patterns
Design multi-agent systems with context isolation, supervisor or swarm coordination, explicit handoffs, parallel execution, and decision frameworks for when multiple agents are justified.
16.9k · bundle
chen-yu-hao pymc-bayesian-modeling
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
5 · bundle