aryan's starred repositories
ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
PythonRobotics
Python sample codes for robotics algorithms.
PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks.
PathPlanning
Common used path planning algorithms with animations.
image-super-resolution
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
EDSR-PyTorch
PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)
neurodiffeq
A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.
a-PyTorch-Tutorial-to-Super-Resolution
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution
mavlink-router
Route mavlink packets between endpoints
motion_planning
Robot path planning, mapping and exploration algorithms
Graph-Matching-Networks
PyTorch implementation of Graph Matching Networks, e.g., Graph Matching with Bi-level Noisy Correspondence (COMMON, ICCV 2023), Graph Matching Networks for Learning the Similarity of Graph Structured Objects (GMN, ICML 2019).
deep-graph-matching-consensus
Implementation of "Deep Graph Matching Consensus" in PyTorch
SLAM_AND_PATH_PLANNING_ALGORITHMS
This repository contains the solutions to all the exercises for the MOOC about SLAM and PATH-PLANNING algorithms given by professor Claus Brenner at Leibniz University. This repository also contains my personal notes, most of them in PDF format, and many vector graphics created by myself to illustrate the theoretical concepts. Hope you enjoy it! :)
pinns-torch
PINNs-Torch, Physics-informed Neural Networks (PINNs) implemented in PyTorch.
Segmentation-of-Ultrasound-Images
The purpose of this study is the contour extraction of a region of interest in ultrasonic images. I applied the anisotropic diffusion algorithm to preprocess images, then an active contour model using a gradient vector flow was employed. In the end, the contour of a lesion area of the ultrasonic images was extracted.
Physics-Informed-Neural-Networks-PyTorch
Implementation of physics informed neural networks with PyTorch
Covid-19-GNN
This repo demonstrates how to accurately predict covid-19 date using a graph neural network with comparison to other traditional data models
sparse-coding
PyTorch implementation, with CUDA support, of the sparse coding algorithm based on the paper by Olshausen and Field (1997).
custom_scripts
Useful custom scripts I use in my setups