grayguy2002

grayguy2002's Stars

• juraam/stable-diffusion-from-scratch

  Implementation of Stable Diffusion with PyTorch

  Language:Jupyter Notebook29318

• huggingface/diffusion-models-class

  Materials for the Hugging Face Diffusion Models Course

  Language:Jupyter Notebook3.6k390

• microsoft/generative-ai-for-beginners

  21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

  Language:Jupyter Notebook64.6k32.9k

• vincentherrmann/pytorch-wavenet

  An implementation of WaveNet with fast generation

  Language:Jupyter Notebook973227

• google-research/magvit

  Official JAX implementation of MAGVIT: Masked Generative Video Transformer

  Language:Python94742

• YuanGongND/ssast

  Code for the AAAI 2022 paper "SSAST: Self-Supervised Audio Spectrogram Transformer".

  Language:Python36460

• karpathy/build-nanogpt

  Video+code lecture on building nanoGPT from scratch

  Language:Python3.5k493

• YuanGongND/ast

  Code for the Interspeech 2021 paper "AST: Audio Spectrogram Transformer".

  Language:Jupyter Notebook1.1k214

• sunyingjian/AI-in-well-logging

  人工智能在石油测井上的应用包括采用机器学习，深度学习等相关方法进行岩性识别与相关测井曲线的回归。The application of artificial intelligence in well logging includes the use of machine learning, deep learning and other related methods for lithology identification and regression of related well logging data.

  Language:Jupyter Notebook12726

• arushi2509/Pseudo-Log-Generation-using-Machine-Learning

  The goal is to develop data-driven models by processing “easy-to-acquire” conventional logs from Well 1 and using the data-driven models to generate synthetic compressional and shear travel-time logs (DTC and DTS, respectively) in Well 2.

  Language:Jupyter Notebook2

• sunyingjian/numpy-

  开源的测井数据集 Open source well logging data set 适用于机器学习分析地下储层岩性识别与分类

  Language:Jupyter Notebook6412

• binary-husky/gpt_academic

  为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。

  Language:Python65.2k8k

• GistNoesis/FourierKAN

  Language:Python70458

• Blealtan/efficient-kan

  An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).

  Language:Python4k359

• KindXiaoming/pykan

  Kolmogorov Arnold Networks

  Language:Jupyter Notebook15k1.4k

• fstrnad/pyDRLinWESM

  A small package for using Deep Reinforcement Learning within World-Earth System Models

  Language:Python82

• lu-group/deeponet-fno

  DeepONet & FNO (with practical extensions)

  Language:Python21549

• The-AI-Summer/Hugging_Face_tutorials

  Hugging Face tutorials

  Language:Python147

• tintn/vision-transformer-from-scratch

  A Simplified PyTorch Implementation of Vision Transformer (ViT)

  Language:Jupyter Notebook13723

• nlp-with-transformers/notebooks

  Jupyter notebooks for the Natural Language Processing with Transformers book

  Language:Jupyter Notebook3.9k1.2k

• daniel-koehn/Differential-equations-earth-system

  Course material for the lecture "Differential equations in the earth system" (WS 2019/2020) @ CAU Kiel

  Language:Jupyter Notebook3918

• heinerigel/coursera

  Jupyter notebooks for "Computers, Waves, Simulations"

  Language:Jupyter Notebook4540

• neuraloperator/physics_informed

  Language:Python36184

• pranavpatil1/eikonal-tomography-fno-kernel

  Using FNOs to solve the inverse eikonal tomography problem.

  Language:Jupyter Notebook6

• bsciolla/gaussian-random-fields

  Generator of 2D gaussian random fields

  Language:Jupyter Notebook497

• PredictiveIntelligenceLab/Physics-informed-DeepONets

  Language:Jupyter Notebook27287

• OpenBMB/XAgent

  An Autonomous LLM Agent for Complex Task Solving

  Language:Python8.1k833

• pmocz/finitedifference-python

  Finite Difference simulation of the Wave Equation (Double-slit experiment)

  Language:Python20

• vc-bonn/Unsupervised_Deep_Learning_of_Incompressible_Fluid_Dynamics

  Language:Python9222

• Jianxun-Wang/phygeonet

  PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain

  Language:C++8131