:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Polat, Can, Serpedin, Erchin, Kurban, Mustafa, Kurban, Hasan
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Materials Science Computational Engineering, Finance, and Science
Online Access:	https://arxiv.org/abs/2601.22312
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Stress-Testing Multimodal Foundation Models for Crystallographic Reasoning
by: Polat, Can, et al.
Published: (2025)

Beyond Atomic Geometry Representations in Materials Science: A Human-in-the-Loop Multimodal Framework
by: Polat, Can, et al.
Published: (2025)

Understanding the Capabilities of Molecular Graph Neural Networks in Materials Science Through Multimodal Learning and Physical Context Encoding
by: Polat, Can, et al.
Published: (2025)

How Far Can You Grow? Characterizing the Extrapolation Frontier of Graph Generative Models for Materials Science
by: Polat, Can, et al.
Published: (2026)

C2NP: A Benchmark for Learning Scale-Dependent Geometric Invariances in 3D Materials Generation
by: Polat, Can, et al.
Published: (2026)

QuantumCanvas: A Multimodal Benchmark for Visual Learning of Atomic Interactions
by: Polat, Can, et al.
Published: (2025)

Exploring Various Sequential Learning Methods for Deformation History Modeling
by: Yatkin, Muhammed Adil, et al.
Published: (2025)

xChemAgents: Agentic AI for Explainable Quantum Chemistry
by: Polat, Can, et al.
Published: (2025)

HalluVerse25: Fine-grained Multilingual Benchmark Dataset for LLM Hallucinations
by: Abdaljalil, Samir, et al.
Published: (2025)

Emerging Microelectronic Materials by Design: Navigating Combinatorial Design Space with Scarce and Dispersed Data
by: Zhang, Hengrui, et al.
Published: (2024)

Learning Latent Hardening (LLH): Enhancing Deep Learning with Domain Knowledge for Material Inverse Problems
by: Tian, Qinyi, et al.
Published: (2025)

polyGen: A Learning Framework for Atomic-level Polymer Structure Generation
by: Jain, Ayush, et al.
Published: (2025)

Micrometer: Micromechanics Transformer for Predicting Mechanical Responses of Heterogeneous Materials
by: Wang, Sifan, et al.
Published: (2024)

Automated Constitutive Model Discovery by Pairing Sparse Regression Algorithms with Model Selection Criteria
by: Urrea-Quintero, Jorge-Humberto, et al.
Published: (2025)

Predicting Grain Growth in Polycrystalline Materials Using Deep Learning Time Series Models
by: Younes, Eliane, et al.
Published: (2025)

IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video
by: Khanbayov, Rasul, et al.
Published: (2026)

Knowing When Not to Answer: Abstention-Aware Scientific Reasoning
by: Abdaljalil, Samir, et al.
Published: (2026)

Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules
by: Segal, Nofit, et al.
Published: (2025)

A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools
by: Van, Minh-Hao, et al.
Published: (2025)

Probabilistic Predictions of Process-Induced Deformation in Carbon/Epoxy Composites Using a Deep Operator Network
by: Kiyani, Elham, et al.
Published: (2025)

A Data-Efficient Sequential Learning Framework for Melt Pool Defect Classification in Laser Powder Bed Fusion
by: Raihan, Ahmed Shoyeb, et al.
Published: (2024)

Deep Kernel Bayesian Optimisation for Closed-Loop Electrode Microstructure Design with User-Defined Properties based on GANs
by: Gayon-Lombardo, Andrea, et al.
Published: (2025)

Physics-based material parameters extraction from perovskite experiments via Bayesian optimization
by: Zhan, Hualin, et al.
Published: (2024)

A Comparison of Surrogate Constitutive Models for Viscoplastic Creep Simulation of HT-9 Steel
by: Robbe, Pieterjan, et al.
Published: (2025)

Advanced Displacement Magnitude Prediction in Multi-Material Architected Lattice Structure Beams Using Physics Informed Neural Network Architecture
by: Mishra, Akshansh
Published: (2024)

Simulation-Free Determination of Microstructure Representative Volume Element Size via Fisher Scores
by: Liu, Wei, et al.
Published: (2024)

From structure mining to unsupervised exploration of atomic octahedral networks
by: Xian, R. Patrick, et al.
Published: (2023)

Atomistic Simulation Guided Convolutional Neural Networks for Thermal Modeling of Friction Stir Welding
by: Mishra, Akshansh
Published: (2025)

Geometric and Topological Deep Learning for Predicting Thermo-mechanical Performance in Cold Spray Deposition Process Modeling
by: Mishra, Akshansh
Published: (2026)

TransDiffSBDD: Causality-Aware Multi-Modal Structure-Based Drug Design
by: Hu, Xiuyuan, et al.
Published: (2025)

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery
by: Hu, Xiuyuan, et al.
Published: (2025)

FluxNet: Learning Capacity-Constrained Local Transport Operators for Conservative and Bounded PDE Surrogates
by: Lan, Zishuo, et al.
Published: (2026)

evoxels: A differentiable physics framework for voxel-based microstructure simulations
by: Daubner, Simon, et al.
Published: (2025)

Physics-Informed GCN-LSTM Framework for Long-Term Forecasting of 2D and 3D Microstructure Evolution
by: Razavi, Hamidreza, et al.
Published: (2025)

Calibrating Scientific Foundation Models with Inference-Time Stochastic Attention
by: Yadav, Akash, et al.
Published: (2026)

Proteo-R1: Reasoning Foundation Models for De Novo Protein Design
by: Wu, Fang, et al.
Published: (2026)

Towards Foundation Model for Chemical Reactor Modeling: Meta-Learning with Physics-Informed Adaptation
by: Wang, Zihao, et al.
Published: (2024)

A collaborative digital twin built on FAIR data and compute infrastructure
by: Deucher, Thomas M., et al.
Published: (2025)

A physics-encoded Fourier neural operator approach for surrogate modeling of divergence-free stress fields in solids
by: Khorrami, Mohammad S., et al.
Published: (2024)

Accelerating and enhancing thermodynamic simulations of electrochemical interfaces
by: Du, Xiaochen, et al.
Published: (2025)