Pinned Repositories
aeolis-python
A process-based model for simulating supply-limited aeolian sediment transport. This fork is focused on an in-progress implementation of sand fences and other coastal management interventions into Aeolis.
BeachPlanformModel
BPM is a Python-based model that predicts the equilibrium beach planform. The model utilizes a reduced-complexity approach to build a shoreline that reflects the spatial variation of offshore wave sheltering along a beach limited by headlands.
bending_stress_ANN
BMI-CSHORE
bmi-example-python
An example of wrapping a model written in Python with a BMI
bmi-live
Code, docs, and Jupyter Notebooks for the BMI Live clinic at the CSDMS Annual Meeting
bmi-prms-demo
Repository contains notebooks to demo PRMS BMIs
bmi-prms6-surface
PRMS6 BMI for surface-zone including all processes above the soil-zone
EquationDiscovery_MDmax_FDmax
PICNN
simulating two-phase Darcy flows in porous media using CNN
lzhu5's Repositories
lzhu5/EquationDiscovery_MDmax_FDmax
lzhu5/PICNN
simulating two-phase Darcy flows in porous media using CNN
lzhu5/BeachPlanformModel
BPM is a Python-based model that predicts the equilibrium beach planform. The model utilizes a reduced-complexity approach to build a shoreline that reflects the spatial variation of offshore wave sheltering along a beach limited by headlands.
lzhu5/bending_stress_ANN
lzhu5/BMI-CSHORE
lzhu5/COCOS
on-the-fly estimation of coastal parameters from video of a wave field
lzhu5/cshore
cshore
lzhu5/BoundaryPhysicsInformedNeuralOperator
lzhu5/Causal-PINN-for-beam
Transfer learning for improved generalizability in causal physics-informed neural networks for beam simulations
lzhu5/cms2d
CMS is a coastal modeling system that couples a wave, circulation, and morphology model together to get better predictions in the near-shore.
lzhu5/Computational_Domain_PINNs
lzhu5/CSHORE-GUI
lzhu5/D3D_add_turbines
MATLAB script for adding tidal turbines to Delft3D models as porous plates
lzhu5/databook_python
IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz
lzhu5/grainsizeanalysis-aeolis
lzhu5/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
lzhu5/handson-ml3
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
lzhu5/Hybrid-PINN
lzhu5/jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
lzhu5/jax-cfd
Computational Fluid Dynamics in JAX
lzhu5/ml-road
Machine Learning Resources, Practice and Research
lzhu5/PINN-TC
Physics-Informed Neural Networks for geophysical fluid flows. This code was used to reconstruct hurricanes based on sparse observations in Eusebi et al. (2023).
lzhu5/PINNpapers
Must-read Papers on Physics-Informed Neural Networks.
lzhu5/pinns-tf2
PINNs-TF2, Physics-informed Neural Networks (PINNs) implemented in TensorFlow V2.
lzhu5/PINNs-TF2.0
TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).
lzhu5/policy_gradients
Pytorch implementation of policy gradient based RL algorithms (VPG, PPO; in-progress: TRPO, DDPG)
lzhu5/pysindy
A package for the sparse identification of nonlinear dynamical systems from data
lzhu5/SediNet
Deep learning framework for optical granulometry (estimation of sedimentological variables from sediment imagery)
lzhu5/the-elements-of-statistical-learning
My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
lzhu5/waveModelSelection
Basic water wave theory