ICLR 2026PastOther
AI for Accelerated Materials Design - ICLR 2026
AI4Mat-ICLR-2026
- Submission deadline
- Feb 2, 2026, 20:00 UTCOpenReview-synced 2026-02-02 20:00 UTC (as of 2026-06-23) — extensions on OpenReview are applied automatically; verify on the website.
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (56)
Fetched from OpenReview (v2) on 2026-06-10.
A Comparative Study of Molecular Dynamics Approaches for Simulating Ionic Conductivity in Solid Lithium Electrolytes
Accelerating Multi-Property Molecular Design via Entropic-Risk-Based Counterfactual Explanations
AI-Guided Closed-Loop Discovery of Hard Multiple Principal Element Alloys
An Experiment-Aware Bayesian Optimization Workflow for Noisy Mixed-Input Settings
An Orbital-based Geometric Deep Learning Framework for Periodic Materials
ASTRA: Statistically Robust Model Selection from Cross-Validation
Benchmarking Augmentation Strategies for LLM-Based Solid-State Synthesis Prediction
Boltzmann Generators for Condensed Matter via Riemannian Flow Matching
CatAgent: Multi-Agent Orchestration for Electrocatalyst Discovery
Challenges and Vision For Standardization of Biopolymer Datasets for Machine Learning
Characterizing Microelectronic Devices via Scalable, Confinement-Aware Equivariant Networks
Comparative Performance of EI-MS Spectrum Prediction Models under Data-scarce and Domain-imbalanced Settings
Context Determines Optimal Architecture in Materials Segmentation
Discovering Out-of-Distribution Superconductors via Reinforcement Learning and Model Merging
Diversity-Aware Pretraining in Materials Learning via Task Similarity
Enforcing Constraints in Molecular and Crystalline Generative Models via Physics-Constrained Flow Matching
Exploring Transfer Learning for Materials Property Prediction
Feedback-Based Learning of Ground State Properties using Tensor Cross Interpolation
FragmentFlow: Scalable Transition State Generation for Large Molecules
Framework-Constrained Materials Generation
From Synthesis to Kinetics: A Data-Driven Deep Learning Framework for Process-Aware Ferroelectric Dynamics
Generative Adversarial Networks for Data Augmentation and Inverse Design of Synthesis Conditions in Perovskite Solar Cells
Geometry-Aware OOD Generalization for Composite Materials
Getting the Data Right: A Physics-Consistent, Calibrated Dataset for SEM-Based Defect Localization in PEM Fuel Cells
Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink
Hierarchy-Guided Topology Latent Flow for Molecular Graph Generation
Information-Theoretic Requirements for Gradient-Based Task Affinity Estimation in Multi-Task Learning
Latent Diffusion Pretraining for Crystal Property Prediction
Learning 4D Material-Interface Dynamics From Few X-RAY Projections
Learning Hamiltonian Flow Maps: Mean Flow Consistency for Large-Timestep Molecular Dynamics
Learning k-Resolved Electronic Structure via Soft Energy Occupancy Prediction
Materials Research Agent
MATRIX: Stress-Testing LLM Reasoning in Materials Science
MatSeek: An Automated Knowledge-Driven Framework for Materials Research
Molecule property prediction with molecular orbitals
MSP-LLM: A Unified Large Language Model Framework for Complete Material Synthesis Planning
NMIRacle: Multi-modal Generative Molecular Elucidation from IR and NMR Spectra
Open Challenges to Unlock Deep Eutectic Solvent Discovery
Open Materials Generation with Inference-Time Reinforcement Learning
Optimizing Materials With CliqueFlowmer
Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach
Property-Guided Molecular Generation and Optimization via Latent Flows
Reasoning-to-Simulation: An Agentic Framework for Discovery of Electrolyte Materials
Robotic Automation Discovery of Biodegradable Electronics via Multimodal Active Learning and AI-Guided Design
Sample Efficient Generative Molecular Optimization with Joint Self-Improvement
Solvaformer: Unified Geometric Learning for Solubility-Aware Automated Synthesis
Synergistic Multi-Task Learning for Electronic Density of States Prediction
SynReason: Enhancing Synthesis Reasoning via Reinforcement Learning Experimental Feedback
Synthesis-constrained molecular design with direct optimization of reaction conditions
Test-Time Tuned Language Models Enable End-to-end De Novo Molecular Structure Generation from MS/MS Spectra
Text-Twin-Translation (T$^{3}$): A Full-Stack Machine Learning Framework for Functional Material-Device Systems Discovery
The Benchmarking Void: A Roadmap for Domain-Adapted Computer Vision in Fuel Cell Defect Detection
Topology-Aware Neural Graph Operator (TANGO) for Material Constitutive Laws
Towards Intelligent Manufacturing: Spatio-Temporal Learning of Process–Material Dynamics with Attention-Driven Neural Operators
Train Separately, Compose at Sampling: Multi-Property Crystal Generation with Orthogonal Flow Guidance
When Does Context Help? A Systematic Study of Target-Conditional Molecular Property Prediction