neural network quantization

Overcoming Oscillations in Quantization-Aware Training ICML 2022 Redistribution of Weights and Activations for AdderNet Quantization NeurIPS 2022 Training Quantised Neural Networks With STE Variants: The Additive Noise Annealing Algorithm CVPR 2022 A Greedy Algorithm for Quantizing Neural Networks JMLR 2021 Any-Precision Deep Neural Networks AAAI 2021 Automated Log-Scale Quantization for Low-Cost Deep Neural Networks CVPR 2021 BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction ICLR 2021 BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization ICLR 2021 CAT: Compression-Aware Training for bandwidth reduction JMLR 2021 Demystifying and Generalizing BinaryConnect NeurIPS 2021 Distribution Adaptive INT8 Quantization for Training CNNs AAAI 2021 Distribution-Aware Adaptive Multi-Bit Quantization CVPR 2021 Diversifying Sample Generation for Accurate Data-Free Quantization CVPR 2021 Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference ICML 2021 DPOQ: Dynamic Precision Onion Quantization ACML 2021 HAWQ-V3: Dyadic Neural Network Quantization ICML 2021 Learnable Companding Quantization for Accurate Low-Bit Neural Networks CVPR 2021 Learning Frequency Domain Approximation for Binary Neural Networks NeurIPS 2021 Mirror Descent View for Neural Network Quantization AISTATS 2021 OPQ: Compressing Deep Neural Networks with One-shot Pruning-Quantization AAAI 2021 Optimal Quantization Using Scaled Codebook CVPR 2021 Permute, Quantize, and Fine-Tune: Efficient Compression of Neural Networks CVPR 2021 RMSMP: A Novel Deep Neural Network Quantization Framework With Row-Wise Mixed Schemes and Multiple Precisions ICCV 2021 Robust error bounds for quantised and pruned neural networks L4DC 2021 Scalable Verification of Quantized Neural Networks AAAI 2021