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6.034_fall_15

Codes for 6.034 Artificial Intelligence 15'

aenet

Atomic interaction potentials based on artificial neural networks

algorithm

automatminer

An automatic engine for predicting materials properties.

cnn_gradient_analysis

Train a convolutional neural network and analyze the gradients in the model to identify relationships in high dimensional spaces.

conditional-gan

Tensorflow implement for Conditional convolutional adversarial networks.

cs228-material

Teaching materials for the probabilistic graphical models and deep learning classes at Stanford

deep-learning-experiments

Notes and experiments to understand deep learning concepts

dl_computefest_2017

Harvard Computefest 2017 Deep Learning workshops

forcefield_template

A template repo for disseminating force fields with foyer

gan-intro

ganhacks

starter from "How to Train a GAN?" at NIPS2016

gans

Generative Adversarial Networks implemented in PyTorch and Tensorflow

generative-models

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

hybrid-perovskites

DFT optimised crystal structures of inorganic and hybrid halide perovskites

kervolution

Kervolution Library in PyTorch (CVPR 2019)

mapidoc

Public repo for Materials API documentation

matgenb

Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.

matminer

data mining for Materials Science

mit-6.034

Problem set of MIT Artificial Intelligence 6.034 Fall 2017

mit-artificial-intelligence--6.034-

Assignment Solutions to MIT AI Fall 2016

ml_bandstructure

Machine learning III-V band structure on alchemical prediction

molfc

A package for the computation of electronic spectra in the harmonic approximation.

mosdef_tutorials

A set of tutorials to introduce new users to the MoSDeF (Molecular Simulation Design Framework) toolkit

neural-fingerprint

Convolutional nets which can take molecular graphs of arbitrary size as input.

nn_robust_attacks

Robust evasion attacks against neural network to find adversarial examples

proxylessnas

[ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware. https://arxiv.org/abs/1812.00332

pyorigintools

documentation and abstraction classes for interacting with OriginLab through PyOrigin

pytopomat

Python Topological Materials (pytopomat) is a code for easy, high-throughput analysis of topological materials.

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers