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3D Molecule Generation
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Scalable Non-Equivariant 3D Molecule Generation via Rotational Alignment
Applications of Modular Co-Design for De Novo 3D Molecule Generation
Scalable Autoregressive 3D Molecule Generation
GEOM-Drugs Revisited: Toward More Chemically Accurate Benchmarks for 3D Molecule Generation
Towards Unified Latent Space for 3D Molecular Latent Diffusion Modeling
Straight-Line Diffusion Model for Efficient 3D Molecular Generation
ReQFlow: Rectified Quaternion Flow for Efficient and High-Quality Protein Backbone Generation
NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation
BoKDiff: Best-of-K Diffusion Alignment for Target-Specific 3D Molecule Generation
Score-based 3D molecule generation with neural fields
D3MES: Diffusion Transformer with multihead equivariant self-attention for 3D molecule generation
Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation
LMDM:Latent Molecular Diffusion Model For 3D Molecule Generation
Text-guided Diffusion Model for 3D Molecule Generation
Covariance-Adaptive Sequential Black-box Optimization for Diffusion Targeted Generation
BInD: Bond and Interaction-generating Diffusion Model for Multi-objective Structure-based Drug Design
Fast 3D Molecule Generation via Unified Geometric Optimal Transport
Mixed Continuous and Categorical Flow Matching for 3D De Novo Molecule Generation
ControlMol: Adding Substructure Control To Molecule Diffusion Models
Unified Generative Modeling of 3D Molecules via Bayesian Flow Networks
Geometric-Facilitated Denoising Diffusion Model for 3D Molecule Generation
Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for 3D Molecule Generation
Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation
Shape-conditioned 3D Molecule Generation via Equivariant Diffusion Models
Directional diffusion models for graph representation learning
3D molecule generation by denoising voxel grids
Learning Subpocket Prototypes for Generalizable Structure-based Drug Design
Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation
Generation of 3D Molecules in Pockets via Language Model
MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation
Geometric Latent Diffusion Models for 3D Molecule Generation
GraphVF: Controllable Protein-Specific 3D Molecule Generation with Variational Flow
Geometry-Complete Diffusion for 3D Molecule Generation and Optimization
Graph Generation with Diffusion Mixture
Equivariant Energy-Guided SDE for Inverse Molecular Design
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.