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adnuts

An R package for NUTS sampling using ADMB

arviz

Exploratory analysis of Bayesian models with Python

autograd

Efficiently computes derivatives of numpy code.

awesome-neural-ode

A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.

bayesian-neural-networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

bayesian_ground_motion_selection

These are a set of codes for simulating the Conditional Spectrum using a Bayesian Analysis. Simulated ground motions can be conveniently combined with real ground motion data through these codes. For more information, please refer to "A Bayesian Treatment of the Conditional Spectrum Approach for Ground Motion Selection". Report by Somayajulu Dhulipala and Madeleine Flint.

bayesiandeeplearning

bbp

SCEC Broadband Platform

bbvi

A collection of Black Box Variational Inference algorithms implemented in an object-oriented Python framework using Autograd.

bihnns

The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs) used with state-of-the-art sampling schemes like Hamiltonian Monte Carlo (HMC) and the No-U-Turn-Sampler (NUTS).

blackbear

BlackBear is a MOOSE-based code for simulating degradation processes in concrete and other structural materials.

bnt

Bayes Net Toolbox for Matlab

complex_systems_rnn

constrained-hamiltonian-neural-networks

deeponet

Learning nonlinear operators via DeepONet

deepxde

A library for scientific machine learning and physics-informed learning

diffusion

Denoising Diffusion Probabilistic Models

disf_hazard

This repo consists of the codes used for a paper titled "DISFUNCTIONALITY HAZARD: A RISK-BASED TOOL TO SUPPORT THE RESILIENT DESIGN OF SYSTEMS SUBJECTED TO SINGLE HAZARDS AND MULTIHAZARDS."

earthquake_intensity_measure_sufficiency

These are the codes for IM selection paper.

falcon

Fracturing And Liquid CONservation

freefem-doc

FreeFEM user documentation

frg_publications

Publications from FRG

gnn-powerflow

Graph Neural Network application in predicting AC Power Flow calculation. Developed with Pytorch Geometric framework. My Master Thesis at Eindhoven University of Technology

gpmat

Matlab implementations of Gaussian processes and other machine learning tools.

graphneuralsolver

hamiltonian-nn

Code for our paper "Hamiltonian Neural Networks"

hamiltonian_networks

Hamiltonian Neural Networks for solving Differential Equations

heteroscedasticity

igapack-phasefield

Second and fourth-order adaptive phase field modeling of fracture using PHT-splines in the framework of IGA.

kernel_seismicrisk