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Profil bibliographique

Wenbing Huang

Informations fournies par OpenAlex. Research Africa ne déduit ni nationalité, ni poste, ni coordonnées personnelles.

256Publications signalées
9699Citations signalées
6Affiliations récentes

Les institutions déclarées

Les domaines associés

Advanced Graph Neural NetworksMachine Learning in Materials ScienceAdvanced Neural Network ApplicationsMultimodal Machine Learning ApplicationsComputational Drug Discovery Methods

Les publications récentes

Accès ouvert 2026 conference-paper OpenAlex

DMFlow: Disordered Materials Generation by Flow Matching

Liming Wu, Rui Jiao, Q Li, Mingze Li et autres

The design of materials with tailored properties is crucial for technological progress. However, most deep generative models focus exclusively on perfectly ordered crystals, neglecting the important class of disordered materials. To address this gap, we introduce DMFlow, a generative framework specifically designed …

cn (code pays fourni par la source)

0 citations
Accès ouvert 2026 conference-paper OpenAlex

One Path to Model Them All: Learnable-Time Flow Matching for Crystal Structure and Energy Prediction

Songyou Li, Mingze Li, Qianpu Liu, Jiacheng Cen et autres

Crystals are cornerstone materials for semiconductors and renewable energy, yet their discovery is hindered by the prohibitive cost of Density Functional Theory (DFT). While geometric graph neural networks have advanced Crystal Structure Prediction (CSP) and energy estimation, existing methods treat these tasks …

cn (code pays fourni par la source)

0 citations
Accès ouvert 2026 article OpenAlex

A Survey of Graph Transformers: Architectures, Theories and Applications

Erçan E. Kuruoğlu, Liang Wang, Tingyang Xu, Wenbing Huang et autres

Graph Transformers (GTs) have demonstrated a strong capability in modeling graph structures by addressing the intrinsic limitations of graph neural networks (GNNs), such as over-smoothing and over-squashing. Recent studies have proposed diverse architectures, enhanced explainability, and practical applications for Graph Transformers. In …

hk, cn, it, ky (code pays fourni par la source)

4 citations ACM Computing Surveys
Accès ouvert 2026 article OpenAlex

Siamese foundation models for crystal structure prediction

Li‐Ming Wu, Wenbing Huang, Liwei Liu, Yipeng Zhou et autres

Abstract Predicting crystal structures from chemical compositions is a fundamental challenge in materials discovery, complicated by complex 3D geometries that distinguish it from fields like protein folding. Here, we present Diffusion-based crystAl Omni (DAO), a pretrain-finetune framework for crystal structure prediction integrating …

cn, us (code pays fourni par la source)

1 citation Nature Communications
Accès ouvert 2026 preprint OpenAlex

Programming Biomolecular Interactions with All-Atom Generative Model

Xiangzhe Kong, Junwei Chen, Ziting Zhang, Gaodeng Li et autres

ABSTRACT Biomolecular interactions lie at the core of cellular life, spanning diverse molecular modalities from small molecules to nucleic acids and proteins. Nevertheless, design strategies remain separated despite shared physicochemical principles of molecular recognition. Here we present AnewOmni, a unified generative framework …

cn, us, ch, at (code pays fourni par la source)

3 citations bioRxiv (Cold Spring Harbor Laboratory)
Accès ouvert 2025 article OpenAlex

Powder diffraction crystal structure determination using generative models

Q Li, Rui Jiao, Liming Wu, Wenbing Huang et autres

Accurate crystal structure determination is critical across all scientific disciplines involving crystalline materials. However, solving and refining crystal structures from powder X-ray diffraction (PXRD) data is traditionally a labor-intensive process that demands substantial expertise. Here we introduce PXRDGen, an end-to-end neural network …

cz, cn, us (code pays fourni par la source)

15 citations Nature Communications

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