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Neural Network Compression

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Showing 1–50 of 193 papers

TitleStatusHype
DepGraph: Towards Any Structural PruningCode4
Torch2Chip: An End-to-end Customizable Deep Neural Network Compression and Deployment Toolkit for Prototype Hardware Accelerator DesignCode2
Data-Free Learning of Student NetworksCode2
Neural Network Compression Framework for fast model inferenceCode2
A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and RecommendationsCode2
Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-Constrained Edge Computing SystemsCode1
SwiftTron: An Efficient Hardware Accelerator for Quantized TransformersCode1
Prune Your Model Before Distill ItCode1
ZeroQ: A Novel Zero Shot Quantization FrameworkCode1
Towards Meta-Pruning via Optimal TransportCode1
The continuous categorical: a novel simplex-valued exponential familyCode1
Distilled Split Deep Neural Networks for Edge-Assisted Real-Time SystemsCode1
PD-Quant: Post-Training Quantization based on Prediction Difference MetricCode1
CHIP: CHannel Independence-based Pruning for Compact Neural NetworksCode1
WoodFisher: Efficient Second-Order Approximation for Neural Network CompressionCode1
Robustness and Transferability of Universal Attacks on Compressed ModelsCode1
Quantisation and Pruning for Neural Network Compression and RegularisationCode1
Spectral Tensor Train Parameterization of Deep Learning LayersCode1
T-Basis: a Compact Representation for Neural NetworksCode1
Neural network compression via learnable wavelet transformsCode1
Wavelet Feature Maps Compression for Image-to-Image CNNsCode1
Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and BetterCode1
NeRV: Neural Representations for VideosCode1
FAT: Learning Low-Bitwidth Parametric Representation via Frequency-Aware TransformationCode1
Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint ReductionCode1
REST: Robust and Efficient Neural Networks for Sleep Monitoring in the WildCode1
SPIN: An Empirical Evaluation on Sharing Parameters of Isotropic NetworksCode1
Learning Filter Basis for Convolutional Neural Network CompressionCode1
An Overview of Neural Network Compression—0
Adaptive Error-Bounded Hierarchical Matrices for Efficient Neural Network Compression—0
A Comprehensive Survey on Model Quantization for Deep Neural Networks in Image Classification—0
A Novel Structure-Agnostic Multi-Objective Approach for Weight-Sharing Compression in Deep Neural Networks—0
DP-Net: Dynamic Programming Guided Deep Neural Network Compression—0
Efficient and Robust Knowledge Distillation from A Stronger Teacher Based on Correlation Matching—0
A novel channel pruning method for deep neural network compression—0
Cascaded Projection: End-to-End Network Compression and Acceleration—0
A Comparative Study of Neural Network Compression—0
Build a Compact Binary Neural Network through Bit-level Sensitivity and Data Pruning—0
Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data—0
A Bayesian Optimization Framework for Neural Network Compression—0
Distilling Pixel-Wise Feature Similarities for Semantic Segmentation—0
DKM: Differentiable K-Means Clustering Layer for Neural Network Compression—0
Data-Free Knowledge Distillation with Soft Targeted Transfer Set Synthesis—0
Balanced and Deterministic Weight-sharing Helps Network Performance—0
Data-Driven Low-Rank Neural Network Compression—0
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds—0
Automatic Parameter Tying in Neural Networks—0
An Efficient Real-Time Object Detection Framework on Resource-Constricted Hardware Devices via Software and Hardware Co-design—0
Deep Neural Network Compression for Aircraft Collision Avoidance Systems—0
AcceRL: Policy Acceleration Framework for Deep Reinforcement Learning—0
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