Lists (32)
Adversarial Network
Adversarial Training
adversarial training methodAnomaly Detection
Anomaly Detection reference code and paperAudio Classification
Audio ClassificationBayesian Machine Learning
book list
c++ study : data structure
data structure and algorithm studyCalibration
Chemistry-GNN
Using GNN to analyze chemical propertiesComputer Vision
Computer Vision paper and reference codeCS interview
코딩 인터뷰 대비Distributed-GPU-Training
distributed gpu training reference codeetc
Explainable AI
GNN
GNN based reference code and paperImbalanced dataset
Technique for imbalanced datasetImitation learning
Machine Learning
meta-learning
ML pipeline
Machine Learning pipeline and MLopsMLops
About MLops(or Devops)Model compression
Distillation + PruningMulti-Modal Machine Learning
Neural ODE
Neural Operator
NLP
NLP reference code and paperNumerical method
Optimization
- Optimization for Machine LearningParallel-Computing
parallel computing reference codePhysics
Computational physics and Physics-informed machine learningReinforcement Learning
Reinforcement Learning Reference code and papertime series
Stars
Genetic Algorithm for integer constrained optimization and its applications
Code for the paper "Auto differentiable Ensemble Kalman Filters" (https://arxiv.org/abs/2107.07687), accepted for publication in SIAM Journal on Mathematics of Data Science (SIMODS)
A collection of ensemble square root kalman filters implemented in Python
Kalman Filter implementation in Python using Numpy only in 30 lines.
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoo…
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
Code Implementation of AdjointDiffusion: a physics-guided and fabrication-aware optimization of photonic devices
course material for the "Notebooks to Scripts to Packages" workshop as part of Princeton Wintersession 2023
Python Notebook for a "geometric multigrid solver"
Version-control CVs/resumes as source code
Riemannian optimization on the symplectic Stiefel manifold
From the paper "Dynamic mode decomposition for multiscale nonlinear physics" by Dylewsky, Tao, & Kutz
POD and DMD decomposition of data from fluid dynamics. This work has been produced during my internship at the von Karman Institute for Fluid Dynamics under supervision of Professor Miguel A. Mendez.
AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)
Supporting codes for the numerical implementations in the paper "Operator inference for non-intrusive model reduction with quadratic manifolds" by Rudy Geelen, Stephen Wright and Karen Willcox
Example codes for Plasma Simulations by Example, CRC Press, 2019
PICSP - (Particle-in-Cell Simulation of Plasma) is an open-source scientific program for simulating plasmas using the Particle-In-Cell (PIC) method on a structured mesh.
🌌 A collaborative list of awesome software for exploring Physics concepts
The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural Networks (DNNs), Neural ODEs, and Symplectic Neural Networks…
Symplectic neural networks for learning dynamics of Hamiltonian systems from data.
In this work, we present a novel approach that combines the power of Koopman operators and deep neural networks to generate a linear representation of the Duffing oscillator. This approach enables…