google/brain-tokyo-workshop resource

Health v2 · maintenance only

Flags: no_releases archived

Adoption not part of the score

1285 stars · 335 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of research code releases from Google Brain's Tokyo team, including projects on weight agnostic neural networks, neuroevolution, attention-based agents, and evolution strategies with CLIP. It accompanies published papers with runnable implementations in Jupyter Notebook and Python.

Use cases

• reproduce weight agnostic neural network research
• learn neuroevolution for reinforcement learning agents
• run attention-based self-interpretable agents on car racing environments
• fit concrete images with evolution strategies and CLIP
• study permutation-invariant neural networks for RL
• explore world models without forward prediction

When to choose

• you want reference implementations of published Google Brain Tokyo research papers
• you are studying neuroevolution, evolution strategies, or attention-based RL agents
• you need a starting point for research extensions like CarRacing variants

When to avoid

• you need a production-ready or maintained ML library with API stability
• you want a single cohesive framework rather than separate research codebases
• you need official Google support or long-term updates

Facets

learning-resource · maturity maintenance

machine-learning reinforcement-learning simulation machine-learning reinforcement-learning artificial-intelligence tutorials python cross-platform research-code neuroevolution evolution-strategies google-brain neural-networks jupyter-notebook

Member repositories

For agents

markdown · JSON · MCP: product_card(name="google/brain-tokyo-workshop")