swaroophangal

swaroophangal

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Location:India

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swaroophangal's repositories

Applied-Deep-Learning

Applied Deep Learning Course

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Art-of-Code-A-pythonic-approach

This repository is a part of an online course taken by me for School kids to teach them the fundamental idea behind programming and computer science. This course was primarily taught using Python.

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Attitude-Estimation

MatLAB and Python implementations for 6-DOF IMU attitude estimation using Kalman Filters, Complementary Filters, etc.

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awesome-competitive-programming

:gem: A curated list of awesome Competitive Programming, Algorithm and Data Structure resources

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awesome-control-theory

Awesome resources for learning control theory

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awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

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Awesome-LLM

Awesome-LLM: a curated list of Large Language Model

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awesome-network-analysis

A curated list of awesome network analysis resources.

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esplocalizer

ESP8266 with IMU, Barometer and Battery

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awesome-research

A curated list of resources to help with computational research.

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espusb

Software-only ESP8266 USB Device

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HadesFCS

Complete flight control system designed from scratch. Hardware designed with KiCad.

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librobotcontrol

Robotics Focused library for embedded Linux computers.

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LifeEngine

The Life Engine

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mandelbrotnn

Torturing neural networks by forcing them to learn the Mandelbrot set.

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markdown_readme

Markdown - you can mark up titles, lists, tables, etc., in a much cleaner, readable and accurate way if you do it with HTML.

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mlconservation_code

Neural network solvers for differential equations with exact conservation laws

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pde_neural_operators

Frame invariance and scalability of neural operators for partial differential equations

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Physics_Informed_NeuralNetwork

Implementation in TF 2.0 of Maziar Raissi's Physics Informed Neural Networks (PINNs) repository.

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PINNpapers

Must-read Papers on Physics-Informed Neural Networks.

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PINNs-based-MPC

We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-informed neural networks (PINNs) are a promising tool to approximate (partial) differential equations. PINNs are not suited for control tasks in their original form since they are not designed to handle variable contro

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pytorch-cpp

C++ Implementation of PyTorch Tutorials for Everyone

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pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

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rotors_simulator

RotorS is a UAV gazebo simulator

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SPINN

Sparse Physics-based and Interpretable Neural Networks

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tfc

The Theory of Functional Connections: A functional interpolation method with applications in solving differential equations.

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Voronoi-CNN

Sample codes for training of Voronoi-tessellation-assisted convolutional neural network by Fukami et al. (Nature Machine Intelligence 2021)

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