seongsukim-ml

2021F_Monte_Carlo

The practice and review of the Monte-Carlo method for Statistical Physics, especially for the Ising model.

2022_CMBP

My own codes and calculation for internship in CMBP Laboratory in GIST.

AIRS

algorithm-training

The repository of problem solving (especially algorithm problems of computer science)

alignn

Atomistic Line Graph Neural Network

AutoEquiv

Group Equivariant Linear Maps

Competent-programming

This repository is made for preparing competent programming.

DeepDream_Pytorch

DeepDream_Pytorch

GPWNO

Gaussain plane-wave neural operator (GPWNO) is a novel approach to predict the electron density of molecule, combining two types of the bases: Gaussian-type orbital and plane-wave.

Monte-Carlo-Method-on-2D-Ising-Model

The result of the 2021 winter research internship at Computational Many Body Physics lab in GIST

seongsukim-ml/GPWNO

Gaussain plane-wave neural operator (GPWNO) is a novel approach to predict the electron density of molecule, combining two types of the bases: Gaussian-type orbital and plane-wave.

seongsukim-ml/2022_CMBP

My own codes and calculation for internship in CMBP Laboratory in GIST.

seongsukim-ml/AIRS

seongsukim-ml/alignn

Atomistic Line Graph Neural Network

seongsukim-ml/Monte-Carlo-Method-on-2D-Ising-Model

The result of the 2021 winter research internship at Computational Many Body Physics lab in GIST

seongsukim-ml/canonical_network

seongsukim-ml/cond-cdvae

seongsukim-ml/Crystal_GNN_Workspace

seongsukim-ml/DB_DiffCSP

Database generation by DiffCSP

seongsukim-ml/DiffCSP

[NeurIPS 2023] The implementation for the paper "Crystal Structure Prediction by Joint Equivariant Diffusion"

seongsukim-ml/DiffDock

Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

seongsukim-ml/dp-cdvae

Diffusion Probabilistic CDVAE

seongsukim-ml/equiformer

[ICLR'23 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

seongsukim-ml/equiformer_v2

[arXiv'23] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

seongsukim-ml/equivariant-zoo

The implementation of the state-of-the-art and brand-new equivariant models. Most models are related to the geometric GNNs.

seongsukim-ml/equivariant_crystal_networks

Code for the paper Equivariant Networks for Crystal Structures

seongsukim-ml/EwaldMP

Reference implementation of "Ewald-based Long-Range Message Passing for Molecular Graphs" (ICML 2023)

seongsukim-ml/faenet

seongsukim-ml/gcnn_keras

Graph convolution with tf.keras

seongsukim-ml/GeoDiff

Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).

seongsukim-ml/globe

Reference implementation of "Generalizing Neural Wave Functions" (ICML 2023)

seongsukim-ml/InfGCN-pytorch

Official implementation of the NeurIPS 23 spotlight paper of ♾️InfGCN♾️.

seongsukim-ml/kss_homepage

seongsukim-ml/MDsim

[TMLR 2023] Training and simulating MD with ML force fields

seongsukim-ml/mycdvae

An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]

seongsukim-ml/PGCGM

Source code for generating materials with 20 space groups using PGCGM

seongsukim-ml/seml_logger

A small utility class to enable easy logging with Aim and TensorBoardX for experiments managed via `seml`

seongsukim-ml/seongsukim-ml.github.io

seongsukim-ml/symd

N-Dimensional MD engine with symmetry group constraints

seongsukim-ml/SymMagCDVAE

generate materials with symmetry