Yuvarajendra Anjaneya Reddy's Projects
MATLAB codes for calculating the forces on a delta wing and boundary layer profiles
CMU 24-787 Artificial Intelligence and Machine Learning Project: A Machine Learning Framework for Predicting Errors in the Numerical Solutions of Navier-Stokes Equations
This project aims on designing a logistics UAV for transportation of medical goods.
🧑🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Applied Deep Learning Course
A curated list of awesome Deep Learning tutorials, projects and communities.
This repository contains the scripts and preprocessed data to recreate the figures and results presented in the paper: A Comprehensive Review of Digital Twin - Part 2: Roles of Uncertainty Quantification and Optimization, a Battery Digital Twin, and Perspectives
Discretization of elements or a material using FEM (Finite Element Method)
A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
Learning two-phase microstructure evolution using neural operators and autoencoder architectures
coarse-to-fine variational optical flow method for fluid flows
Constraint sizing diagram plays a vital part during the preliminary design stages of an aircraft or a fixed wing UAV. The diagram is generated with the help of preliminary estimates or specifications that are determined or derived based on the mission, nature of the build of an aircraft and functions of it.
Let us control diffusion models!
Keras-tensorflow code for training a frame-by-frame binary classifier with video input + code for computing targets.
Repository with the programming assignments from Introduction to Machine Learning Course of Duke University on Coursera.
code for performing active flow control of the 2D Karman street using Deep Reinforcement Learning
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Speed estimation from a single dashboard camera using Deep Convolutional Networks
DeepCFD: Efficient Steady-State Laminar Flow Approximation with Deep Convolutional Neural Networks
DeepTrack-2.0
Calculate forces on a delta wing (Delta plate is used for simplification)
Common functions for augmenting data to train deep optical flow models in PyTorch.
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
Pytorch implementation of FlowNet by Dosovitskiy et al.
Accelerating Eulerian Fluid Simulation With Convolutional Networks
Use Fourier transform to learn operators in differential equations.
A new one shot face swap approach for image and video domains
Code accompanying my blog post: So, what is a physics-informed neural network?