udemirezen

ann-visualizer

A python library for visualizing Artificial Neural Networks (ANN)

characterizing-pinns-failure-modes

Characterizing possible failure modes in physics-informed neural networks.

DPM

Official code for DPM : A Novel Training Method for Physics-Informed Neural Networks in Extrapolation

PINN-1

Simple PyTorch Implementation of Physics Informed Neural Network (PINN)

pinn_corrosion_fatigue

Python scripts for physics-informed neural networks for corrosion-fatigue prognosis

pinn_wind_bearing

Python scripts for wind turbine main bearing fatigue life estimation with physics-informed neural networks

relative_balancing

rtl_tool_kit

universal_differential_equations

Repository for the Universal Differential Equations for Scientific Machine Learning paper, describing a computational basis for high performance SciML

W-PINNs-DE-Hydrodynamic-Shock-Tube-Problems

*PyTorch Implementation* Solving Hydrodynamic Shock-Tube Problems Using Weighted Physics-Informed Neural Networks with Domain Extension (Papados, 2021)

udemirezen/arctic-research

udemirezen/ADA-F

Anti-Derivatives Approximator from Fourier series expansion

udemirezen/AutoKoopman

AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.

udemirezen/awesome-deep-snn

A curated list of awesome deep spiking neural networks projects

udemirezen/awesome-snn-conference-paper

🔥 This repo collects summit papers, codes about Spiking Neural Networks for anyone who wants to do research on it. We are continuously improving the project.

udemirezen/Awesome-Spiking-Neural-Networks1

A paper list of spiking neural networks, including papers, codes, and related websites.

udemirezen/Awesome-Spiking-Neural-Networks2

Awesome Spiking Neural Networks

udemirezen/DeepOpLearn

Repository for a presentation on Deep Operator Learning / DeepONets

udemirezen/engression

udemirezen/Georgia_GIA

udemirezen/icenet-paper

Code associated with the paper 'Seasonal Arctic sea ice forecasting with probabilistic deep learning'

udemirezen/igm

Instructed Glacier Model (IGM)

udemirezen/lca-pytorch

Sparse coding in PyTorch via the Locally Competitive Algorithm (LCA)

udemirezen/Learning-Python-Physics-Informed-Machine-Learning-PINNs-DeepONets

Physics Informed Machine Learning Tutorials (Pytorch and Jax)

udemirezen/mccarthy

my slides, notes, and codes on numerical glacier and ice sheet modeling, for the International Summer School in Glaciology, McCarthy, AK

udemirezen/nn-frequency-shortcuts

Frequency Shortcuts in Neural Networks

udemirezen/ODINN.jl

Global glacier model using Universal Differential Equations for climate-glacier interactions

udemirezen/PI-DeepONet

Implementing a physics-informed DeepONet from scratch

udemirezen/PINN-for-ExtremeMechanics

udemirezen/pinn_clusters

Accompanying code for paper: "1D Ice Shelf Hardness Inversion: Clustering Behavior and Collocation Resampling in Physics-Informed Neural Networks." Code for training PINNs for 1D ice-shelf inverse modeling and analysis of training results over repeated trials.

udemirezen/PINNs-for-education

Deep Learning for Solving Differential Equations (Educational)

udemirezen/pinns-torch

PINNs-Torch, Physics-informed Neural Networks (PINNs) implemented in PyTorch.

udemirezen/PyBaMM

Fast and flexible physics-based battery models in Python

udemirezen/search_fundamentals_course

Public repository for the Search Fundamentals course taught by Daniel Tunkelang and Grant Ingersoll. Available at https://corise.com/course/search-fundamentals?utm_source=daniel

udemirezen/SNN-Tutorial-with-snnTorch

The snnTorch tutorial series is based on the Jason K. Eshraghian, Max Ward, Emre Neftci, Xinxin Wang, Gregor Lenz, Girish Dwivedi, Mohammed Bennamoun, Doo Seok Jeong, and Wei D. Lu. "Training Spiking Neural Networks Using Lessons From Deep Learning". arXiv preprint arXiv:2109.12894, September 2021.

udemirezen/snntorch-learning

Learning about snnTorch

udemirezen/snntorch-LSM

udemirezen/snntorch_tutorial_zh

个人翻译官方 snntorch tutorial

udemirezen/spikingNeuralNetworks_exploration

Code used to analyse the dependance of spiking neural network on initial conditions using snnTorch. The results are presented in my Bachelors Thesis: "The impact of initial parameters on the learning of spiking neural networks".

udemirezen/thermal-nn

Thermal Neural Networks. Application to an electric motor.