sjiang87's Stars
zavalab/ML
Monge88/SGVAE
aspuru-guzik-group/chemical_vae
Code for 10.1021/acscentsci.7b00572, now running on Keras 2.0 and Tensorflow
KirillShmilovich/ActiveLearningCG
Some codes for "Discovery of Self-Assembling pi-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation"
yuanqidu/GraphGT
graph4ai/graph4nlp
Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources!
seokhokang/graphvae_approx
Efficient Learning of Non-Autoregressive Graph Variational Autoencoders for Molecular Graph Generation
davide-belli/generative-graph-transformer
PyTorch implementation of "Image-Conditioned Graph Generation for Road Network Extraction"
snap-stanford/GraphRNN
JiaxuanYou/graph-generation
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
razvanmarinescu/EB1A
EB1A Full Application - I-140 and I-485
jingraham/neurips19-graph-protein-design
Generative Models for Graph-Based Protein Design
drorlab/gvp-pytorch
Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure
jules-leguy/EvoMol
Evolutionary algorithm for molecular properties optimization
wengong-jin/hgraph2graph
Hierarchical Generation of Molecular Graphs using Structural Motifs
yunshengtian/DGEMO
[NeurIPS 2020] Diversity-Guided Efficient Multi-Objective Optimization With Batch Evaluations
thuml/Autoformer
About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008
thuml/Time-Series-Library
A Library for Advanced Deep Time Series Models.
RILAB/statements
Successful Job Applications and Grants
deephyper/nas-gcn
Neural Architecture Search for Graph-Convolution Neural Networks using DeepHyper.
keisuke198619/supervisedDMD
Supervised Dynamic Mode Decomposition (Supervised DMD)