aliakhav

gym

A toolkit for developing and comparing reinforcement learning algorithms.

caffe

Caffe: a fast open framework for deep learning.

fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

DeepLearning

machine-learning-articles

🧠💬 Articles I wrote about machine learning, archived from MachineCurve.com.

Applied-Deep-Learning

Applied Deep Learning Course

pytorchTutorial

PyTorch Tutorials from my YouTube channel

deeptime

Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation

WeatherBench

A benchmark dataset for data-driven weather forecasting

pytorch-examples

transformer_network

Spatial Transformer network

recurrent-spatial-transformer-code

Code for Recurrent Spatial Transformer Networks

smarties

Lightweight and scalable framework for Reinforcement Learning

tensorflow-course

Tensorflow Beginner Course from my YouTube channel

turbulence-codes

Curated list of some open-source codes for turbulent flow simulations, including turbulent multiphase, turbulent reacting flows, turbulent convection and turbulent atmospheric physics.

mkl_fft

NumPy-based Python interface to Intel (R) MKL FFT functionality

p3dfft

P3DFFT stands for Parallel Three-Dimensional Fast Fourier Transforms. It is a library for large-scale computer simulations on parallel platforms. It implements 3D FFT and related algorithms such as Chebyshev transform (an important class of algorithm for simulations in a wide range of fields). P3DFFT uses 2D, or pencil, decomposition. For more information:

PINN-wss

PINN for obtaining WSS from sparse data

pygpu-workshop

PINN-examples

Examples implementing physics-informed neural networks (PINN) in Pytorch

DAFI

DAFI: Ensemble based data assimilation and field inversion, repository for internal development

MARL_LES

Repository for data and scripts of "Automating Turbulence Modeling by Multi-Agent Reinforcement Learning"

relexi

A scalable reinforcement learning framework for CFD on HPC systems

lesTools

A toolbox for the construction and assessment of subgrid-scale models for large-eddy simulations

Deep-Learning-Turbulence-model

Use deep learning to learn a turbulence model from high fedelity data. The model can reasonably predict other turbulent flows.

subgridtransportNN

PyTorch implementation of Subgrid Transport Neural Network

CubismUP_3D

Uniform resolution solver for incompressible 3D NS eq. in velocity-pressure formulation with multiple non-divergence-free self-propelled obstacles.

PyMLMC

2D-DDP

CNN and CNN w/ transfer learning

Airfoil_EE