Cover Image

Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Segal, Nofit, Netanyahu, Aviv, Greenman, Kevin P., Agrawal, Pulkit, Gomez-Bombarelli, Rafael
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Materials Science Computational Engineering, Finance, and Science Chemical Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Loss Landscape of Powder X-Ray Diffraction-Based Structure Optimization Is Too Rough for Gradient Descent
by: Segal, Nofit, et al.
Published: (2025)

Symmetry-Constrained Generation of Diverse Low-Bandgap Molecules with Monte Carlo Tree Search
by: Subramanian, Akshay, et al.
Published: (2024)

Corrosion of metal reinforcements within concrete and localisation of supporting reactions under natural conditions
by: Hageman, T., et al.
Published: (2025)

A computational framework to predict weld integrity and microstructural heterogeneity: application to hydrogen transmission
by: Wijnen, J., et al.
Published: (2024)

MLIP Arena: Advancing Fairness and Transparency in Machine Learning Interatomic Potentials via an Open, Accessible Benchmark Platform
by: Chiang, Yuan, et al.
Published: (2025)

Predicting the impact of water transport on carbonation-induced corrosion in variably saturated reinforced concrete
by: Korec, E., et al.
Published: (2024)

The role of chemo-mechanical modelling in the development of battery technology -- a perspective
by: Boyce, A., et al.
Published: (2024)

Computational predictions of hydrogen-assisted fatigue crack growth
by: Cui, C., et al.
Published: (2024)

Coupled thermo-chemo-mechanical phase field-based modelling of hydrogen-assisted cracking in girth welds
by: Castro, L., et al.
Published: (2026)

Computational predictions of weld structural integrity in hydrogen transport pipelines
by: Mandal, T. K., et al.
Published: (2024)

On the suitability of single-edge notch tension (SENT) testing for assessing hydrogen-assisted cracking susceptibility
by: Cupertino-Malheiros, L., et al.
Published: (2024)

A mesoscale phase-field model of intergranular liquid lithium corrosion of ferritic/martensitic steels
by: Lhoest, A., et al.
Published: (2025)

Phase field modelling of cracking and capacity fade in core-shell cathode particles for lithium-ion batteries
by: Tu, Y., et al.
Published: (2025)

A microstructure-sensitive electro-chemo-mechanical phase-field model of pitting and stress corrosion cracking
by: Makuch, M., et al.
Published: (2024)

Virtual failure assessment diagrams for hydrogen transmission pipelines
by: Wijnen, J., et al.
Published: (2025)

Influence of concentration-dependent material properties on the fracture and debonding of electrode particles with core-shell structure
by: Tu, Y., et al.
Published: (2024)

Phase-field simulations opening new horizons in corrosion research
by: Martínez-Pañeda, E.
Published: (2024)

Can dents and gouges compromise the structural integrity of hydrogen transport pipelines?
by: Das, R., et al.
Published: (2026)

On the role of crack electrolyte wetting in the degradation and performance of battery active particles
by: Luza-Vega, S., et al.
Published: (2026)

Hybrid Machine Learning for Enhanced Prediction of Diffusion Coefficients in Liquids
by: Wagner, Jens, et al.
Published: (2026)

A recipe for scalable attention-based MLIPs: unlocking long-range accuracy with all-to-all node attention
by: Qu, Eric, et al.
Published: (2026)

Multi-task learning for molecular electronic structure approaching coupled-cluster accuracy
by: Tang, Hao, et al.
Published: (2024)

Relative frequencies of constrained events in stochastic processes: An analytical approach
by: Rusconi, S., et al.
Published: (2024)

Molecular Representations for AI in Chemistry and Materials Science: An NLP Perspective
by: JP, Sanjanasri, et al.
Published: (2026)

GradNav: Accelerated Exploration of Potential Energy Surfaces with Gradient-Based Navigation
by: Ock, Janghoon, et al.
Published: (2024)

Unravelling the interplay between steel rebar corrosion rate and corrosion-induced cracking of reinforced concrete
by: Korec, E., et al.
Published: (2024)

TDS Simulator: A MATLAB App to model temperature-programmed hydrogen desorption
by: García-Macías, E., et al.
Published: (2024)

Mathematical modelling of flow and adsorption in a gas chromatograph
by: Cabrera-Codony, A., et al.
Published: (2024)

Dynamic Modeling of Precipitation in Electrolyte Systems
by: Kemmerling, Niklas, et al.
Published: (2025)

AtomDisc: An Atom-level Tokenizer that Boosts Molecular LLMs and Reveals Structure--Property Associations
by: Zhang, Mingxu, et al.
Published: (2025)

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

A Synthesizability-Guided Pipeline for Materials Discovery
by: Prein, Thorben, et al.
Published: (2025)

Reasoning-Driven Retrosynthesis Prediction with Large Language Models via Reinforcement Learning
by: Zhang, Situo, et al.
Published: (2025)

Discovery of Novel Reticular Materials for Carbon Dioxide Capture using GFlowNets
by: Cipcigan, Flaviu, et al.
Published: (2023)

Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials
by: Nam, Juno, et al.
Published: (2024)

Material Fingerprinting: A shortcut to material model discovery without solving optimization problems
by: Flaschel, Moritz, et al.
Published: (2025)

Learning Ordering in Crystalline Materials with Symmetry-Aware Graph Neural Networks
by: Peng, Jiayu, et al.
Published: (2024)

High-Performance Gradient Evaluation for Complex Soft Materials Using MPI-based DFS Algorithm
by: Bhattacharyya, Anurag
Published: (2025)

A Physics-Enforced Neural Network to Predict Polymer Melt Viscosity
by: Jain, Ayush, et al.
Published: (2024)

Graph-Network-Based Predictive Modeling for Highly Cross-Linked Polymer Systems
by: Lee, Wonseok, et al.
Published: (2023)