Copertina

Histogram-Equalized Quantization for logic-gated Residual Neural Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Nguyen, Van Thien, Guicquero, William, Sicard, Gilles
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Hardware Architecture
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights
di: Nguyen, Van Thien, et al.
Pubblicazione: (2025)

BILLNET: A Binarized Conv3D-LSTM Network with Logic-gated residual architecture for hardware-efficient video inference
di: Nguyen, Van Thien, et al.
Pubblicazione: (2025)

End-to-end fully-binarized network design: from Generic Learned Thermometer to Block Pruning
di: Nguyen, Thien, et al.
Pubblicazione: (2025)

RCNet: $ΔΣ$ IADCs as Recurrent AutoEncoders
di: Verdant, Arnaud, et al.
Pubblicazione: (2025)

Exploring Quantization and Mapping Synergy in Hardware-Aware Deep Neural Network Accelerators
di: Klhufek, Jan, et al.
Pubblicazione: (2024)

MCEL: Margin-Based Cross-Entropy Loss for Error-Tolerant Quantized Neural Networks
di: Yayla, Mikail, et al.
Pubblicazione: (2026)

On-Chip Hardware-Aware Quantization for Mixed Precision Neural Networks
di: Huang, Wei, et al.
Pubblicazione: (2023)

Exploring the Limitations of Kolmogorov-Arnold Networks in Classification: Insights to Software Training and Hardware Implementation
di: Tran, Van Duy, et al.
Pubblicazione: (2024)

Neural Network Quantization for Microcontrollers: A Comprehensive Survey of Methods, Platforms, and Applications
di: Abushahla, Hamza A., et al.
Pubblicazione: (2025)

Accelerating PoT Quantization on Edge Devices
di: Saha, Rappy, et al.
Pubblicazione: (2024)

AXELRAM: Quantize Once, Never Dequantize
di: Nishida, Yasushi
Pubblicazione: (2026)

RESQ: A Unified Framework for REliability- and Security Enhancement of Quantized Deep Neural Networks
di: Mohammadi, Ali Soltan, et al.
Pubblicazione: (2026)

LOTION: Smoothing the Optimization Landscape for Quantized Training
di: Kwun, Mujin, et al.
Pubblicazione: (2025)

KLLM: Fast LLM Inference with K-Means Quantization
di: Wu, Xueying, et al.
Pubblicazione: (2025)

FaTRQ: Tiered Residual Quantization for LLM Vector Search in Far-Memory-Aware ANNS Systems
di: Zhang, Tianqi, et al.
Pubblicazione: (2026)

ITA: An Energy-Efficient Attention and Softmax Accelerator for Quantized Transformers
di: İslamoğlu, Gamze, et al.
Pubblicazione: (2023)

PQA: Exploring the Potential of Product Quantization in DNN Hardware Acceleration
di: AbouElhamayed, Ahmed F., et al.
Pubblicazione: (2023)

Approximate Multiplier Induced Error Propagation in Deep Neural Networks
di: Alahakoon, A. M. H. H., et al.
Pubblicazione: (2025)

Graph Neural Networks Based Analog Circuit Link Prediction
di: Pan, Guanyuan, et al.
Pubblicazione: (2025)

Efficient and Mathematically Robust Operations for Certified Neural Networks Inference
di: Geyer, Fabien, et al.
Pubblicazione: (2024)

Sustainable Transformer Neural Network Acceleration with Stochastic Photonic Computing
di: Afifi, S., et al.
Pubblicazione: (2026)

Accelerating Sparse Graph Neural Networks with Tensor Core Optimization
di: Wu, Ka Wai
Pubblicazione: (2024)

A 1Mb mixed-precision quantized encoder for image classification and patch-based compression
di: Nguyen, Van Thien, et al.
Pubblicazione: (2025)

EVA: Accelerating LLM Decoding via an Efficient Vector Quantization Architecture
di: Duan, Bowen, et al.
Pubblicazione: (2026)

Layer-wise Weight Selection for Power-Efficient Neural Network Acceleration
di: Fang, Jiaxun, et al.
Pubblicazione: (2025)

PhotoGAN: Generative Adversarial Neural Network Acceleration with Silicon Photonics
di: Suresh, Tharini, et al.
Pubblicazione: (2025)

Efficient VQ-QAT and Mixed Vector/Linear quantized Neural Networks
di: Gou, Terry, et al.
Pubblicazione: (2026)

Algorithmic Strategies for Sustainable Reuse of Neural Network Accelerators with Permanent Faults
di: Alama, Youssef A. Ait, et al.
Pubblicazione: (2024)

NeuraLUT: Hiding Neural Network Density in Boolean Synthesizable Functions
di: Andronic, Marta, et al.
Pubblicazione: (2024)

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices
di: Yan, Minghao, et al.
Pubblicazione: (2023)

FPGA Co-Design for Efficient N:M Sparse and Quantized Model Inference
di: Hsieh, Fen-Yu, et al.
Pubblicazione: (2025)

Binary Weight Multi-Bit Activation Quantization for Compute-in-Memory CNN Accelerators
di: Zhou, Wenyong, et al.
Pubblicazione: (2025)

Exploration of Activation Fault Reliability in Quantized Systolic Array-Based DNN Accelerators
di: Taheri, Mahdi, et al.
Pubblicazione: (2024)

SigmaQuant: Hardware-Aware Heterogeneous Quantization Method for Edge DNN Inference
di: Liu, Qunyou, et al.
Pubblicazione: (2026)

FuncGNN: Learning Functional Semantics of Logic Circuits with Graph Neural Networks
di: Zhao, Qiyun
Pubblicazione: (2025)

Accelerating Neural Networks for Large Language Models and Graph Processing with Silicon Photonics
di: Afifi, Salma, et al.
Pubblicazione: (2024)

ARTEMIS: A Mixed Analog-Stochastic In-DRAM Accelerator for Transformer Neural Networks
di: Afifi, Salma, et al.
Pubblicazione: (2024)

The prediction of the quality of results in Logic Synthesis using Transformer and Graph Neural Networks
di: Yang, Chenghao, et al.
Pubblicazione: (2022)

CNN-Based Equalization for Communications: Achieving Gigabit Throughput with a Flexible FPGA Hardware Architecture
di: Ney, Jonas, et al.
Pubblicazione: (2024)

MixDiT: Accelerating Image Diffusion Transformer Inference with Mixed-Precision MX Quantization
di: Kim, Daeun, et al.
Pubblicazione: (2025)