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Single-step retrosynthesis
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Accelerating the inference of string generation-based chemical reaction models for industrial applications
RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNets
UAlign: Pushing the Limit of Template-free Retrosynthesis Prediction with Unsupervised SMILES Alignment
Node-Aligned Graph-to-Graph (NAG2G): Elevating Template-Free Deep Learning Approaches in Single-Step Retrosynthesis
RetroBridge: Modeling Retrosynthesis with Markov Bridges
Models Matter: The Impact of Single-Step Retrosynthesis on Synthesis Planning
G-MATT: Single-step Retrosynthesis Prediction using Molecular Grammar Tree Transformer
Mind the Retrosynthesis Gap: Bridging the divide between Single-step and Multi-step Retrosynthesis Prediction
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning
MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction
Modeling Diverse Chemical Reactions for Single-step Retrosynthesis via Discrete Latent Variables
G2GT: Retrosynthesis Prediction with Graph to Graph Attention Neural Network and Self-Training
Root-aligned SMILES: A Tight Representation for Chemical Reaction Prediction
SemiRetro: Semi-template framework boosts deep retrosynthesis prediction
RetroComposer: Composing Templates for Template-Based Retrosynthesis Prediction
Permutation invariant graph-to-sequence model for template-free retrosynthesis and reaction prediction
Dual-view Molecule Pre-training
Modern Hopfield Networks for Few- and Zero-Shot Reaction Template Prediction
Energy-based View of Retrosynthesis
Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits
Learning Graph Models for Retrosynthesis Prediction
A Graph to Graphs Framework for Retrosynthesis Prediction
State-of-the-Art Augmented NLP Transformer models for direct and single-step retrosynthesis
Retrosynthesis Prediction with Conditional Graph Logic Network
Learning to Make Generalizable and Diverse Predictions for Retrosynthesis
Retrosynthetic reaction prediction using neural sequence-to-sequence models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.