wzjialang / MCLDNN

The program of RML2016.10a

#计算机科学#[Remote Sensing] PyTorch implementation for "Remote Sensing Change Detection Based on Multidirectional Adaptive Feature Fusion and Perceptual Similarity"

A Unified Implementation of Several Baseline Deep Learning Models for Automatic Modulation Recognition

#计算机科学#The GitHub repository for the paper "Informer" accepted by AAAI 2021.

A PyTorch implementation of "CoAtNet: Marrying Convolution and Attention for All Data Sizes"

An Efficient Deep Learning Model for Automatic Modulation Recognition Based on Parameter Estimation and Transformation

Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration (CVPR 2019 Oral)

#大语言模型#🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

#计算机科学#Trax — Deep Learning with Clear Code and Speed

RepViT: Revisiting Mobile CNN From ViT Perspective [CVPR 2024] and RepViT-SAM: Towards Real-Time Segmenting Anything

My solutions to the programming assignments of the Stanford Compiler course.

Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

[CVPRW 21] "BNN - BN = ? Training Binary Neural Networks without Batch Normalization", Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang

S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)

#计算机科学#A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper, Ada and Blackwell GPUs, to provide better performance with lower memory ut...

We introduce a novel approach for parameter generation, named neural network parameter diffusion (p-diff), which employs a standard latent diffusion model to synthesize a new set of parameters