weight quantization

Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance AAAI 2021 Training with Quantization Noise for Extreme Model Compression ICLR 2021 TRQ: Ternary Neural Networks With Residual Quantization AAAI 2021 AdaBits: Neural Network Quantization With Adaptive Bit-Widths CVPR 2020 Adaptive Loss-Aware Quantization for Multi-Bit Networks CVPR 2020 And the Bit Goes Down: Revisiting the Quantization of Neural Networks ICLR 2020 Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks IJCAI 2020 FleXOR: Trainable Fractional Quantization NeurIPS 2020 Gradient ℓ_1 Regularization for Quantization Robustness ICLR 2020 HLHLp: Quantized Neural Networks Training for Reaching Flat Minima in Loss Surface AAAI 2020 LEARNED STEP SIZE QUANTIZATION ICLR 2020 Searching for Low-Bit Weights in Quantized Neural Networks NeurIPS 2020 Soft Threshold Ternary Networks IJCAI 2020 Structured Compression by Weight Encryption for Unstructured Pruning and Quantization CVPR 2020 Towards Accurate Low Bit-Width Quantization with Multiple Phase Adaptations AAAI 2020 Towards Certificated Model Robustness Against Weight Perturbations AAAI 2020 Training Binary Neural Networks through Learning with Noisy Supervision ICML 2020 Training Binary Neural Networks using the Bayesian Learning Rule ICML 2020 Up or Down? Adaptive Rounding for Post-Training Quantization ICML 2020 Analysis of Quantized Models ICLR 2019 Double Viterbi: Weight Encoding for High Compression Ratio and Fast On-Chip Reconstruction for Deep Neural Network ICLR 2019 KCNN: Kernel-wise Quantization to Remarkably Decrease Multiplications in Convolutional Neural Network IJCAI 2019 Learning to Quantize Deep Networks by Optimizing Quantization Intervals With Task Loss CVPR 2019 MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization NeurIPS 2019 Normalization Helps Training of Quantized LSTM NeurIPS 2019