Image de couverture de livre

Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhou, Cai, Chen, Zijie, Li, Zian, Wang, Jike, Jiang, Kaiyi, Li, Pan, Yu, Rose, Zhang, Muhan, Bates, Stephen, Jaakkola, Tommi
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Artificial Intelligence Group Theory Biomolecules
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

GeoRecon: Graph-Level Representation Learning for 3D Molecules via Reconstruction-Based Pretraining
par: Yan, Shaoheng, et autres
Publié: (2025)

Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms
par: Jing, Bowen, et autres
Publié: (2023)

Generative Modeling of Molecular Dynamics Trajectories
par: Jing, Bowen, et autres
Publié: (2024)

Protein FID: Improved Evaluation of Protein Structure Generative Models
par: Faltings, Felix, et autres
Publié: (2025)

AlphaFold Meets Flow Matching for Generating Protein Ensembles
par: Jing, Bowen, et autres
Publié: (2024)

ProxelGen: Generating Proteins as 3D Densities
par: Faltings, Felix, et autres
Publié: (2025)

AI-based Methods for Simulating, Sampling, and Predicting Protein Ensembles
par: Jing, Bowen, et autres
Publié: (2025)

Dirichlet Flow Matching with Applications to DNA Sequence Design
par: Stark, Hannes, et autres
Publié: (2024)

ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids
par: Stark, Hannes, et autres
Publié: (2025)

Pi-SAGE: Permutation-invariant surface-aware graph encoder for binding affinity prediction
par: Banerjee, Sharmi, et autres
Publié: (2025)

Deep Confident Steps to New Pockets: Strategies for Docking Generalization
par: Corso, Gabriele, et autres
Publié: (2024)

Fragment-Masked Diffusion for Molecular Optimization
par: Li, Kun, et autres
Publié: (2024)

Graph Diffusion Transformers for Multi-Conditional Molecular Generation
par: Liu, Gang, et autres
Publié: (2024)

Reimagining Target-Aware Molecular Generation through Retrieval-Enhanced Aligned Diffusion
par: Xu, Dong, et autres
Publié: (2025)

Improving Protein Optimization with Smoothed Fitness Landscapes
par: Kirjner, Andrew, et autres
Publié: (2023)

Enhancing the efficiency of protein language models with minimal wet-lab data through few-shot learning
par: Zhou, Ziyi, et autres
Publié: (2024)

Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products
par: Luo, Shengjie, et autres
Publié: (2024)

Enhancing Molecular Design through Graph-based Topological Reinforcement Learning
par: Zhang, Xiangyu
Publié: (2024)

Canonicalization of the E value from BLAST similarity search -- dissimilarity measure and distance function for a metric space of protein sequences
par: Mao, Boryeu
Publié: (2025)

Decoding Polyphenol-Protein Interactions with Deep Learning: From Molecular Mechanisms to Food Applications
par: Liu, Qiang, et autres
Publié: (2025)

Comprehensive Insights into the Cholesterol-Mediated Modulation of Membrane Function through Molecular Dynamics Simulations
par: Khodadadi, Ehsaneh, et autres
Publié: (2025)

Graph Neural Networks in Modern AI-aided Drug Discovery
par: Zhang, Odin, et autres
Publié: (2025)

RiboDiffusion: Tertiary Structure-based RNA Inverse Folding with Generative Diffusion Models
par: Huang, Han, et autres
Publié: (2024)

Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion
par: Gao, Bowen, et autres
Publié: (2024)

Instruction-Based Molecular Graph Generation with Unified Text-Graph Diffusion Model
par: Xiang, Yuran, et autres
Publié: (2024)

Discovery of novel antimicrobial peptides with notable antibacterial potency by a LLM-based foundation model
par: Wang, Jike, et autres
Publié: (2024)

Molecular Diffusion Models with Virtual Receptors
par: Halfon, Matan, et autres
Publié: (2024)

AutoLoop: a novel autoregressive deep learning method for protein loop prediction with high accuracy
par: Wang, Tianyue, et autres
Publié: (2025)

DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization
par: Zhou, Xiangxin, et autres
Publié: (2024)

Rethinking Molecular Design: Integrating Latent Variable and Auto-Regressive Models for Goal Directed Generation
par: Arthur-Loui, Heath, et autres
Publié: (2024)

Advancing biomolecular understanding and design following human instructions
par: Zhuang, Xiang, et autres
Publié: (2024)

Rethinking Drug-Drug Interaction Modeling as Generalizable Relation Learning
par: Xu, Dong, et autres
Publié: (2026)

Unveiling Scaling Behaviors in Molecular Language Models: Effects of Model Size, Data, and Representation
par: Xu, Dong, et autres
Publié: (2026)

Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design
par: Klarner, Leo, et autres
Publié: (2024)

Accelerating Inference in Molecular Diffusion Models with Latent Representations of Protein Structure
par: Dunn, Ian, et autres
Publié: (2023)

Towards Efficient Molecular Property Optimization with Graph Energy Based Models
par: Miglior, Luca, et autres
Publié: (2025)

Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space
par: Ketata, Mohamed Amine, et autres
Publié: (2024)

DecoyDB: A Dataset for Graph Contrastive Learning in Protein-Ligand Binding Affinity Prediction
par: Zhang, Yupu, et autres
Publié: (2025)

Understanding Molecular Basis of PTPN11-Related Diseases
par: Um, Seungha, et autres
Publié: (2025)

Steering Protein Family Design through Profile Bayesian Flow
par: Gong, Jingjing, et autres
Publié: (2025)