Awesome cond-mat.soft

Papers

Understanding Structural Representation in Foundation Models for Polymers (2025)
Nathaniel H. Park et al.
1.56
Learning noisy tissue dynamics across time scales (2025)
Ming Han et al.
1.44
Graph Contrastive Learning versus Untrained Baselines: The Role of Dataset Size (2025)
Smayan Khanna et al.
1.39
Global graph features unveiled by unsupervised geometric deep learning (2025)
Mirja Granfors et al.
1.06
Accelerating the identification of informative reduced representations of proteins with deep learning for graphs (2020)
Federico Errica et al.
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Machine Learning for Phase Behavior in Active Matter Systems (2020)
Austin R. Dulaney and John F. Brady
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Encoding protein dynamic information in graph representation for functional residue identification (2021)
Yuan Chiang et al.
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Fast solver for diffusive transport times on dynamic intracellular networks (2022)
Lachlan Elam et al.
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Rotation-equivariant Graph Neural Networks for Learning Glassy Liquids Representations (2022)
Francesco Saverio Pezzicoli et al.
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Narrow escape in composite domains forming heterogeneous networks (2022)
Fr\'ed\'eric Paquin-Lefebvre et al.
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Generative Pretrained Autoregressive Transformer Graph Neural Network applied to the Analysis and Discovery of Novel Proteins (2023)
Markus J. Buehler
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A cyclical route linking fundamental mechanism and AI algorithm: An example from tuning Poisson's ratio in amorphous networks (2023)
Changliang Zhu et al.
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Learning Dynamics from Multicellular Graphs with Deep Neural Networks (2024)
Haiqian Yang et al.
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Accelerating Scientific Discovery with Generative Knowledge Extraction, Graph-Based Representation, and Multimodal Intelligent Graph Reasoning (2024)
Markus J. Buehler
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Similarity Equivariant Graph Neural Networks for Homogenization of Metamaterials (2024)
Fleur Hendriks (1) et al.
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Graph Neural Network-State Predictive Information Bottleneck (GNN-SPIB) approach for learning molecular thermodynamics and kinetics (2024)
Ziyue Zou et al.
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