Ricardo Chin (roaked)

roaked

Geek Repo

Company:Technische Universität Graz

Location:Graz, Austria

Home Page:ricardochin.com

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Ricardo Chin's repositories

battery-degradation-forecast

pybamm framework for battery simulation

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redbull-drone-computer-vision

modeling system dynamics incl. actuators and continuous / discrete controller designs in MATLAB Simulink integrated computer vision using segmentation

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autonomous-vehicle-system-identification

modeling autonomous guided vehicle using MATLAB Simulink. deterministic and stochastic system identification

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hamiltonian-paths

cool Fortran implementation of linked lists for traversing through nodes and finding the hamiltonian path (dynamically)

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robotics-kinematics-dynamics-and-control

kinematics, newton-euler dynamics and centralized/decentralized control of a KUKA robotic gripper -- up next safe reinforcement learning with optimistic exploration instead of trajectory planning. 2019

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snake-evolutionary-reinforcement-learning

parameter optimization of a reinforcement learning deep Q network with memory replay buffer using genetic algorithm in the snake game. base code for snake env from codecamp

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AdditiveManufacturing-CURA

3D printer / slicing GUI built on top of the Uranium framework

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BayesianOptimization

A Python implementation of global optimization with gaussian processes

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carla

Open-source simulator for autonomous driving research.

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deap-evolutionary-computation

Distributed Evolutionary Algorithms in Python

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fake-news-machine-learning-fuzzy-inference

detecting fake news using linguistic features. ML techniques ranging from hard and soft-clustering to fuzzy inference systems and neural networks. included FMID5 - Fuzzy Model Identification toolbox in MATLAB

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finite-element-method-math-formulation

implementing a computational finite element program based on Prandtl stress partial differential equation for linearly analyzing torsional loading problems. C++ woulda been better for scalability

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fun-shell-scripts

where to ski in winter

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genetic-algorithm-optimization

bin packing problem best fit and metaheuristics. genetic algorithm, bonus particle swarm optimization. comparing both algorithms

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hugo-book

Hugo documentation theme as simple as plain book

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imitation

Clean PyTorch implementations of imitation and reward learning algorithms

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leetcode-codeforces

some of the solutions for leetcode problems. some have multiple solutions depending on the algorithms and data structures used, good use cases for programming lectures

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mit-deep-learning

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

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nonlinear-opt-pattern-search-phd

keywords: nonlinear optimization, pattern search, augmented lagrangian, karush-kuhn-tucker, constrained optimization, conjugate gradient methods, quasi newton methods, line search descent methods, onedimensional and multidimensional optimazation

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programming-lectures

my lectures for beginner, intermediate, advanced programming courses. working on the algorithms based on the book 'Grokking Algorithms'. soon: coding for data scientists, pandas, numpy, scipy

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pymc

Bayesian Modeling and Probabilistic Programming in Python

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pytorch-classification-uncertainty

This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"

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reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

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roaked

GitHub config files

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roaked.github.io

personal webpage for a researcher

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RoboticsAlgorithm-Visualization

Python sample codes for robotics algorithms

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spotify-downloader

Download your Spotify playlists and songs along with album art and metadata (from YouTube if a match is found).

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structure-from-motion-computer-vision

structure from motion (SfM) is the process of estimating the 3D structure of a scene from a set of 2D images. here I estimate the poses of a calibrated camera from two images, reconstruct the 3D structure of the scene up to an unknown scale factor, and then recover the actual scale factor by detecting an object of a known

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