Fetching the paper…
Reading the bibliography…
Deep learning has achieved remarkable success in learning representations for molecules, which is crucial for various biochemical applications, ranging from property prediction to drug design.
SMILES, A Chemical Language and Information System. 1. Introduction to Methodology and Encoding Rules
D. Weininger · 1988
Earlier work this paper cites.
The Protein Data Bank
H. M. Berman, J. Westbrook, et al · 2000
Earlier work this paper cites.
On the Art of Compiling and Using ‘Drug-Like’ Chemical Fragment Spaces
J. Degen, C. Wegscheid-Gerlach, et al · 2008
Earlier work this paper cites.
Molecular Descriptors for Chemoinformatics
V. Consonni and R. Todeschini · 2009
Earlier work this paper cites.
ChEMBL: A Large-Scale Bioactivity Database for Drug Discovery
A. Gaulton, L. J. Bellis, et al · 2012
Earlier work this paper cites.
ZINC 15–Ligand Discovery for Everyone
T. Sterling and J. J. Irwin · 2015
Earlier work this paper cites.
Deep Residual Learning for Image Recognition
K. He, X. Zhang, et al · 2016
Earlier work this paper cites.
Molecular Graph Convolutions: Moving Beyond Fingerprints
S. Kearnes, K. McCloskey, et al · 2016
Earlier work this paper cites.
Conformation Generation: The State of the Art
P. C. D. Hawkins · 2017
Earlier work this paper cites.
Semi-Supervised Classification with Graph Convolutional Networks
N. T. Kipf and M. Welling · 2017
Earlier work this paper cites.
SchNet: A Continuous-Filter Convolutional Neural Network for Modeling Quantum Interactions
K. Schütt, P.-J. Kindermans, et al · 2017
Earlier work this paper cites.
Attention is All You Need
A. Vaswani, N. Shazeer, et al · 2017
Earlier work this paper cites.
Pubchem Bioassay: 2017 Update
Y. Wang, S. H. Bryant, et al · 2017
Earlier work this paper cites.
Graph Attention Networks
P. Velickovic, G. Cucurull, et al · 2018
Earlier work this paper cites.
MoleculeNet: A Benchmark for Molecular Machine Learning
Z. Wu, B. Ramsundar, et al · 2018
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
J. Devlin, M. Chang, et al · 2019
Earlier work this paper cites.
Learning Deep Representations by Mutual Information Estimation and Maximization
R. D. Hjelm, A. Fedorov, et al · 2019
Earlier work this paper cites.
SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery
S. Honda, S. Shi, et al · 2019
Earlier work this paper cites.
Evolving Concept of Activity Cliffs
D. Stumpfe, H. Hu, et al · 2019
Earlier work this paper cites.
Deep Graph Infomax
P. Velickovic, W. Fedus, et al · 2019
Earlier work this paper cites.
SMILES-BERT: Large Scale Unsupervised Pre-Training for Molecular Property Prediction
S. Wang, Y. Guo, et al · 2019
Earlier work this paper cites.
How Powerful are Graph Neural Networks?
K. Xu, W. Hu, et al · 2019
Earlier work this paper cites.
Language Models are Few-Shot Learners
T. B. Brown, B. Mann, et al · 2020
Earlier work this paper cites.
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction
S. Chithrananda, G. Grand, et al · 2020
Earlier work this paper cites.
Principal Neighbourhood Aggregation for Graph Nets
G. Corso, L. Cavalleri, et al · 2020
Earlier work this paper cites.
Contrastive Multi-View Representation Learning on Graphs
K. Hassani and A. H. K. Ahmadi · 2020
Earlier work this paper cites.
Denoising Diffusion Probabilistic Models
J. Ho, A. Jain, et al · 2020
Earlier work this paper cites.
Strategies for Pre-training Graph Neural Networks
W. Hu, B. Liu, et al · 2020
Earlier work this paper cites.
GPT-GNN: Generative Pre-Training of Graph Neural Networks
Z. Hu, Y. Dong, et al · 2020
Earlier work this paper cites.
Self-Referencing Embedded Strings (SELFIES): A 100% Robust Molecular String Representation
M. Krenn, F. Häse, et al · 2020
Cited alongside, same era.
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
C. Raffel, N. Shazeer, et al · 2020
Cited alongside, same era.
Self-Supervised Graph Transformer on Large-Scale Molecular Data
Y. Rong, Y. Bian, et al · 2020
Cited alongside, same era.
Learning to Simulate Complex Physics with Graph Networks
A. Sanchez-Gonzalez, J. Godwin, et al · 2020
Cited alongside, same era.
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization
F. Sun, J. Hoffmann, et al · 2020
Cited alongside, same era.
Graph Contrastive Learning with Augmentations
Y. You, T. Chen, et al · 2020
Molecular Contrastive Learning with Chemical Element Knowledge Graph
Y. Fang, Q. Zhang, et al · 2022
Closest in time.
MGMAE: Molecular Representation Learning by Reconstructing Heterogeneous Graphs with A High Mask Ratio
J. Feng, Z. Wang, et al · 2022
Closest in time.
Multilingual Molecular Representation Learning via Contrastive Pre-training
Z. Guo, P. K. Sharma, et al · 2022
Closest in time.
GraphMAE: Self-Supervised Masked Graph Autoencoders
Z. Hou, X. Liu, et al · 2022
Closest in time.
Graph Self-supervised Learning with Accurate Discrepancy Learning
D. Kim, J. Baek, et al · 2022
Closest in time.
KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property Prediction
H. Li, D. Zhao, et al · 2022
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
MolGPT: Molecular Generation Using a Transformer-Decoder Model
V. Bagal, R. Aggarwal, et al · 2021
Cited alongside, same era.
OGB-LSC: A large-scale challenge for machine learning on graphs
W. Hu, M. Fey, et al · 2021
Cited alongside, same era.
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development
K. Huang, T. Fu, et al · 2021
Cited alongside, same era.
An Effective Self-Supervised Framework for Learning Expressive Molecular Global Representations to Drug Discovery
P. Li, J. Wang, et al · 2021
Cited alongside, same era.
GraphDTA: Predicting Drug-Target Binding Affinity with Graph Neural Networks
T. Nguyen, H. Le, et al · 2021
Cited alongside, same era.
E(n) Equivariant Graph Neural Networks
V. G. Satorras, E. Hoogeboom, et al · 2021
Cited alongside, same era.
GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction
S. Li, J. Zhou, et al · 2022
Closest in time.
PanGu Drug Model: Learn a Molecule Like a Human
X. Lin, C. Xu, et al · 2022
Closest in time.
Pre-training Molecular Graph Representation with 3D Geometry
S. Liu, H. Wang, et al · 2022
Closest in time.
SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning
G. A. Pinheiro, J. L. Da Silva, et al · 2022
Closest in time.
Molformer: Large Scale Chemical Language Representations Capture Molecular Structure and Properties
J. Ross, B. Belgodere, et al · 2022
Closest in time.
3D Infomax Improves GNNs for Molecular Property Prediction
H. Stärk, D. Beaini, et al · 2022
Closest in time.
Does GNN Pretraining Help Molecular Representation?
R. Sun, H. Dai, et al · 2022
Closest in time.
Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast
Y. Wang, R. Magar, et al · 2022
Closest in time.
MolCLR: Molecular Contrastive Learning of Representations via Graph Neural Networks
Y. Wang, J. Wang, et al · 2022
Closest in time.
ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning
J. Xia, L. Wu, et al · 2022
Closest in time.
SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation
J. Xia, L. Wu, et al · 2022
Closest in time.
MICER: A Pre-Trained Encoder–Decoder Architecture for Molecular Image Captioning
J. Yi, C. Wu, et al · 2022
Closest in time.
Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations
Y. You, T. Chen, et al · 2022
Closest in time.
Accurate Prediction of Molecular Properties and Drug Targets Using a Self-Supervised Image Representation Learning Framework
X. Zeng, H. Xiang, et al · 2022
Closest in time.
A Deep-Learning System Bridging Molecule Structure and Biomedical Text with Comprehension Comparable to Human Professionals
Z. Zeng, Y. Yao, et al · 2022
Closest in time.
Unified 2D and 3D Pre-Training of Molecular Representations
J. Zhu, Y. Xia, et al · 2022
Closest in time.
Featurizations Matter: A Multiview Contrastive Learning Approach to Molecular Pretraining
Y. Zhu, D. Chen, et al · 2022
Closest in time.
Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs
R. Jiao, J. Han, et al · 2023
Closest in time.
Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching
S. Liu, H. Guo, et al · 2023
Closest in time.
Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules
J. Xia, C. Zhao, et al · 2023
Closest in time.
Pre-training via Denoising for Molecular Property Prediction
S. Zaidi, M. Schaarschmidt, et al · 2023
Closest in time.
Uni-Mol: A Universal 3D Molecular Representation Learning Framework
G. Zhou, Z. Gao, et al · 2023
Closest in time.