forXuyx

forXuyx's Stars

• mikekatz04/LATW

  Tutorials and tools for the LATW Workshop

  Language:Jupyter Notebook4026

• hagabbar/cnn_matchfiltering

  Pipeline used for classifying BBH, NSBH, and BNS signals in LIGO data. Code used for "Matching Matched Filtering" paper.

  Language:Python167

• DefTruth/CUDA-Learn-Notes

  🎉 Modern CUDA Learn Notes with PyTorch: CUDA Cores, Tensor Cores, fp32/tf32, fp16/bf16, fp8/int8, flash_attn, rope, sgemm, hgemm, sgemv, warp/block reduce, elementwise, softmax, layernorm, rmsnorm.

  Language:Cuda1.4k157

• gpu-mode/lectures

  Material for gpu-mode lectures

  Language:Jupyter Notebook3k301

• nicolaswilde/cuda-sgemm

  Language:Cuda5117

• PacktPublishing/Hands-On-GPU-Accelerated-Computer-Vision-with-OpenCV-and-CUDA

  Hands-On GPU Accelerated Computer Vision with OpenCV and CUDA, published by Packt

  Language:C++632227

• AudioLLMs/AudioLLM

  Audio Large Language Models

  1307

• bobo0810/LearnDeepSpeed

  DeepSpeed教程 & 示例注释 & 学习笔记 （大模型高效训练）

  Language:Python1151

• odegeasslbc/FastGAN-pytorch

  Official implementation of the paper "Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis" in ICLR 2021

  Language:Python602100

• jiaorunnju/distributed-training-toolkit-with-pytorch

  a code template for distributed training in pytorch

  Language:Python1

• xxcheng0708/pytorch-model-train-template

  pytorch单精度、半精度、混合精度、单卡、多卡（DP / DDP）、FSDP、DeepSpeed模型训练代码，并对比不同方法的训练速度以及GPU内存的使用

  Language:Python7613

• katsura-jp/pytorch-cosine-annealing-with-warmup

  Language:Python44052

• yzyouzhang/ASVspoof2021_AIR

  Official implementation of our ASVspoof 2021 paper, "UR Channel-Robust Synthetic Speech Detection System for ASVspoof 2021"

  Language:Python535

• lixucuhk/Channel-wise-Gated-Res2Net

  Implementation of the paper: Channel-wise Gated Res2Net: Towards Robust Detection of Synthetic Speech Attacks (INTERSPEECH 2021)

  Language:Shell295

• josebeo2016/SCL-Deepfake-audio-detection

  Synthesis speech detection based on vocoder signature extraction with Supervised Contrastive Learning

  Language:Python151

• 3017218062/Universal-Audio-Classification

  https://www.datafountain.cn/competitions/486

  Language:Python6

• rst0070/Rawformer-implementation-anti-spoofing

  Pytorch implementation of "LEVERAGING POSITIONAL-RELATED LOCAL-GLOBAL DEPENDENCY FOR SYNTHETIC SPEECH DETECTION"

  Language:Python271

• yuanmaoxun/Awesome-RGBT-Fusion

  A collection of deep learning based RGB-T-Fusion methods, codes, and datasets. The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Crowd Counting, RGB-T Fusion Tracking.

  34142

• Linfeng-Tang/VIF-Benchmark

  All deep learning-based infrared and visible image fusion algorithms in a whole framework

  Language:Jupyter Notebook15214

• tencent-ailab/bddm

  BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis

  Language:Python22330

• miracleyoo/pytorch-lightning-template

  An easy/swift-to-adapt PyTorch-Lighting template. 套壳模板，简单易用，稍改原来Pytorch代码，即可适配Lightning。You can translate your previous Pytorch code much easier using this template, and keep your freedom to edit all the functions as well. Big-project-friendly as well. No need to rewrite your config in hydra.

  Language:Jupyter Notebook1.3k195

• liuzywen/RGBTCC

  Language:Python351

• iphysresearch/nflows

  Normalizing flows in PyTorch

  2

• iphysresearch/pycbc

  Core package to analyze gravitational-wave data, find signals, and study their parameters. This package was used in the first direct detection of gravitational waves (GW150914), and is used in the ongoing analysis of LIGO/Virgo data.

  2

• iphysresearch/Docker_cadabra2

  Docker image for Cadabra2

  Language:Dockerfile6

• iphysresearch/conformer

  PyTorch implementation of "Conformer: Convolution-augmented Transformer for Speech Recognition" (INTERSPEECH 2020)

  Language:Python2

• iphysresearch/GW_parameter_estimation

  Parameter estimation for gravitational-wave events with deep learning

  Language:Python4

• iphysresearch/megatron-gw

  Based on Megatron-LM framework, achieving gravitational wave denoising and parameter estimation with transformer-based model.

  Language:Python4

• iphysresearch/ggwd

  Use PyCBC / LALSuite to generate synthetic gravitational-wave data (e.g., for machine learning endeavors).

  2

• iphysresearch/GW_PE_prior_sampling

  Sampling with Prior Knowledge for High-dimensional Gravitational-wave Data Analysis

  Language:Python3