Research map / Architectures and efficiency / Quantization
Linear Symmetric Quantization of Neural Networks for Low-precision Integer Hardware
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- SYQ: Learning Symmetric Quantization for Efficient Deep Neural Networks (CVPR 2018 · similarity 0.90)
- Quantization Networks (CVPR 2019 · similarity 0.90)
- HAWQ-V3: Dyadic Neural Network Quantization (ICML 2021 · similarity 0.89)
- Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference (CVPR 2018 · similarity 0.89)
- Efficient Quantization for Neural Networks with Binary Weights and Low Bitwidth Activations (AAAI 2019 · similarity 0.89)
- Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators (ICLR 2024 · similarity 0.88)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
