micahcarroll/uniMASK
Codebase for "Uni[MASK]: Unified Inference in Sequential Decision Problems"
uniMASK helps researchers in reinforcement learning and sequential decision-making to analyze and predict complex patterns in sequences of actions and observations. It takes datasets of sequential decisions (like agent movements in a game or robot actions) and generates models that can predict missing or future parts of these sequences. This tool is for machine learning researchers, especially those working with behavioral cloning, offline reinforcement learning, or sequence modeling.
No commits in the last 6 months.
Use this if you are a researcher developing or evaluating models that learn from sequential data, and you need a flexible way to perform inference and prediction on parts of these sequences.
Not ideal if you are an end-user looking for a pre-built application or a simple API to solve a specific business problem, as this is a research codebase for advanced model development.
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57
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4
Language
Python
License
MIT
Category
Last pushed
Jul 03, 2024
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