Latest Articles for Quantization

EfficientBioAI helps researchers optimize AI models for faster, energy-efficient bioimaging.

New strategies enhance quantization for Vision Transformers, boosting performance and training speed.

A new approach to audio compression reduces file size without losing quality.

A new method improves DNA compression for efficient data storage.

A detailed look at methods for improving neural network efficiency.

NeuroBlend optimizes neural networks for efficiency and speed on hardware devices.

New tools make it easier to run powerful language models on standard hardware.

A look at how in-memory computing is changing data processing.

A new model enhances perception systems for safer autonomous driving.

QBitOpt improves neural network performance by optimizing bitwidth allocations efficiently.

New methods improve language model efficiency without sacrificing performance.

Research is advancing on using DNA as a compact data storage medium.

Learn how tensor compression enhances shared inference strategies in deep learning.

Exploring quantization strategies to improve performance in large language models.

An overview of pruning and quantization methods applied to YOLOv5.

A look at quantization methods and their applications using the Cantor distribution.

MASE simplifies and speeds up ML accelerator development for modern machine learning models.

New methods reduce model size while maintaining performance in computer vision tasks.

New methods improve training speed and accuracy of GNNs using quantization.

Explore how neural methods improve image compression efficiency and quality.

Researchers combine factorization and quantization to improve AI efficiency.

Ternary SVD offers a simpler and efficient way to compress neural networks.

A novel method reduces memory usage and speeds up large language models.

This article examines ways to enhance quantization in deep learning models using TVM.

An overview of line defects in supersymmetric quantum field theories and their implications.

Evol-Q enhances quantization accuracy in Vision Transformers through evolutionary search techniques.

This article examines the relationship between quantum systems and prime numbers.

A method improving mobile image processing through optimized quantization.

A new method enhances super-resolution image quality while reducing computational needs.

New methods optimize deep neural networks for better real-world performance.

New techniques improve performance of Graph Neural Networks in handling large data structures.

This article discusses bias correction for softmax layers in generative models.

A new approach to reduce memory use in neural networks through 4-bit optimizers.

Discover methods to make Vision Transformers more efficient for real-world applications.

Making vision transformers efficient for drones and mobile devices to enhance visual tasks.

New neural networks designed for better performance in resource-limited devices.

Research improves knowledge distillation methods for efficient semantic image segmentation.

Learn how quantization makes AI models cheaper and easier to use.

New techniques improve model efficiency and prediction accuracy using quantized tensor networks.

This study reviews efficient neural network techniques for image analysis in remote sensing.