Stars
Repository for code related to parallel optimization of target ranges
Lightweight toolkit for de novo molecular generation: SMILES & SELFIES tokenizers, CharRNN / MolGPT / VAE models, training, sampling, and MOSES-style metrics.
Code for 10.1021/acscentsci.7b00572, now running on Keras 2.0 and Tensorflow
Some codes for "Discovery of Self-Assembling pi-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation"
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!
Efficient Learning of Non-Autoregressive Graph Variational Autoencoders for Molecular Graph Generation
PyTorch implementation of "Image-Conditioned Graph Generation for Road Network Extraction"
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
Generative Models for Graph-Based Protein Design
Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure
Evolutionary algorithm for the optimization of molecular properties.
Hierarchical Generation of Molecular Graphs using Structural Motifs
[NeurIPS 2020] Diversity-Guided Efficient Multi-Objective Optimization With Batch Evaluations
About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008
A Library for Advanced Deep Time Series Models for General Time Series Analysis.
Neural Architecture Search for Graph-Convolution Neural Networks using DeepHyper.
Supervised Dynamic Mode Decomposition (Supervised DMD)