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- The FORT team has released differentially private Condor data to external researchers in H1 2020. It is known that analyzing DP data via classic statistical models will lead to biased conclusions. We are releasing at-scale statistical models which provide valid inference from DP data.
- A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
- A modular high-level library to train embodied AI agents across a variety of tasks and environments.
- FBPCS (Facebook Private Computation Solutions) leverages secure multi-party computation (MPC) to output aggregated data without making unencrypted, readable data available to the other party or any third parties. Facebook provides impression & opportunity data, and the advertiser provides conversion / outcome data.
- Repository hosting code used to reproduce results in "Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations" (https://arxiv.org/abs/2402.17152).
aepsych
PublicBenchMARL
PublicA collection of MARL benchmarks based on TorchRL- A library for differentiable nonlinear optimization