Data as of Aug 25, 2026 · Based on 3,181,687 AI responses across 10,525 prompts · See how Parse measures this
Opacusopacus.aiOpacus is an open-source PyTorch library that enables training neural networks with differential privacy by wrapping the model, optimizer, and data loader with a PrivacyEngine to inject noise and enforce gradient clipping. It provides scalable per-sample gradient computation that is 10x faster than microbatching, supports most PyTorch models with minimal modification, and offers a modular API for differential privacy research. Developed by Meta Platforms, Inc., Opacus includes extensive docs, tutorials, an API reference, and a public GitHub repository for community contributions.
Sources
arxiv.org shapes more of what AI says about Opacus than any other source, at 31% of its citations.
petronellatech.com · builtin.com · iterate.ai · medium.com
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Synthetic Data Generation Platforms →Where AI ranks Opacus
Excerpts where Opacus appeared in the AI's answer
Opacus: A library by PyTorch that allows for training machine learning models with Differential Privacy (DP-SGD)
Excerpts where Opacus appeared in the AI's answer
Opacus (PyTorch): A PyTorch library developed by Meta for training models with differential privacy.
