mitmath Goto Github PK

18.0002

1806

18.06 course at MIT

18065

18.065/18.0651: Matrix Methods in Data Analysis, Signal Processing, and Machine Learning

18303

18.303 - Linear PDEs course

18330

18.330 Introduction to Numerical Analysis

18335

18.335 - Introduction to Numerical Methods course

18336

18.336 - Fast Methods for Partial Differential and Integral Equations

18337

18.337 - Parallel Computing and Scientific Machine Learning

18337projects

List of Student Projects for 18.337j

18337sp2023-alexander_mercier-extendrandomvariables.jl

Julia package to extend RandomVariables.jl

18337sp2023-alexander_wang-parallel-computing-sciml-rna-aptamer-design

18337sp2023-amin_heyrani_nobari-18337-linakge-project

Code for 18337 project by Amin Heyrani Nobari

18337sp2023-amy_phung-gpuparticlefilter.jl

18337sp2023-andreas_p__mentze-sciml-project-18.337-spring-2023-mit

18337sp2023-axel_feldmann-hss-gpu

18337sp2023-chenyue_lu-18337_fa23_cl

18337sp2023-dariyan_khan-potentiallearning-2.jl

An open source Julia library for active learning of interatomic potentials in atomistic simulations of materials. It incorporates elements of bayesian inference, machine learning, differentiable programming, software composability, and high-performance computing.

18337sp2023-devang_sehgal__anurag_vaidya-shapley_julia

Implement Shapley values for Global Sensitivity Analysis in Julia

18337sp2023-difei_zhang-parallelwolff

18337sp2023-eric_m__stewart-pinnsforsolids

Physics-informed Neural Networks for solving example continuum mechanics problems, for MIT class 18.337.

18337sp2023-hao-wei_pang-reactionmechanismsimulator.jl

The amazing Reaction Mechanism Simulator for simulating large chemical kinetic mechanisms

18337sp2023-harvey_merton-18.337_project

18337sp2023-jackson_warner_burns-xtb-ts-screener

Screening 'likely-to-converge' Transition States partially optimized by XTB

18337sp2023-kerri_lu-18337-anode-project

18337sp2023-kota_kondo-18337

18337sp2023-luca_weishaupt__andrew_zhang-nbody-rl-public

Code repository for the paper "Physics-informed deep Q-learning for n-body simulations"

18337sp2023-marc_davis-yieldtasks

18337sp2023-minsik_cho-potentiallearning.jl

An open source Julia library for active learning of interatomic potentials in atomistic simulations of materials. It incorporates elements of bayesian inference, machine learning, differentiable programming, software composability, and high-performance computing.

18337sp2023-nathan_stover__krystian_ganko-18.337-project-sp2023

Project for Parallel Computing and Scientific Machine Learning course, Spring 2023.

18337sp2023-nicholas_klugman-neurallyapunov.jl

A library for searching for neural Lyapunov functions in Julia.