为GPT/GLM提供图形交互界面，特别优化论文阅读润色体验，模块化设计支持自定义快捷按钮&函数插件，支持代码块表格显示，Tex公式双显示，新增Python和C++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，支持清华chatglm等本地模型

Python and C++ implementation of anisotropic transfer-matrix method (TMM). Based on article Hodgkinson, I. J., Kassam, S., & Wu, Q. H. (1997). Journal of Computational Physics, 133(1) 75-83

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Code Released for URetinex-Net

Simulated polarised photon scattering (using cylindrical optical fibre as source) in anisotropic micro‐sphere solution using Euler Monte Carlo method to compute the Mueller matrix of the medium.

[CVPR 2022] Rethinking Spatial Invariance of Convolutional Networks for Object Counting

Generative deep learning model for inorganic materials

Here, we combine deep learning (cDCGAN) with adjoint optimization (LumOpt) within a single user-friendly application (DeepAdjoint)). Reference: https://pubs.acs.org/doi/10.1021/acsphotonics.2c00968

Harvard CS50 Python — 2022 Solutions

CAIRI Supervised, Semi- and Self-Supervised Visual Representation Learning Toolbox and Benchmark

Master the command line, in one page

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

✏️ Web-based image segmentation tool for object detection, localization, and keypoints

Monochromatic beam interacts with particle population. Using Monte Carlo simulations the progam calculates the spacial and energy distribution of the exiting spectrum.

FMM+RCWA-rigourous coupled wave analysis for different structures

A Github Copilot implemention for Google Colab. Say goodbye to alt tabbing 👋

🔥 💪 Crack-Detection-and-Segmentation-Dataset-for-UAV-Inspection

Harvard CS50x — 2022 Solutions

此仓库将介绍Deep Learning 所需要的基础知识以及NLP方面的模型原理到项目实操 : )

VAE for embankment settlement and pore water pressure predictions

Models and examples built with TensorFlow

Official implementation of paper "Knowledge Distillation from A Stronger Teacher", NeurIPS 2022

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cycleg…

monte-carlo-mie-scattering-polydisperse-particles

This project was about applying data augmentation on images to create a dataset to train the logistic regression model on the augmented images.

Vector image version of Taichi Language Cheatsheet

Self-Supervised Speech/Sound Pre-training and Representation Learning Toolkit