Copertina

Guiding Generative Models to Uncover Diverse and Novel Crystals via Reinforcement Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Park, Hyunsoo, Walsh, Aron
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Computational Physics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Continuous SUN (Stable, Unique, and Novel) Metric for Generative Modeling of Inorganic Crystals
di: Negishi, Masahiro, et al.
Pubblicazione: (2025)

Multi-Objective Quality-Diversity for Crystal Structure Prediction
di: Janmohamed, Hannah, et al.
Pubblicazione: (2024)

Unveiling Imitation Learning: Exploring the Impact of Data Falsity to Large Language Model
di: Cho, Hyunsoo
Pubblicazione: (2024)

CrystalREPA: Transferring Physical Priors from Universal MLIPs to Crystal Generative Models
di: Zhang, Chengqian, et al.
Pubblicazione: (2026)

Enhancing Quantum Memory Lifetime with Measurement-Free Local Error Correction and Reinforcement Learning
di: Park, Mincheol, et al.
Pubblicazione: (2024)

Quantum Reinforcement Learning-Guided Diffusion Model for Image Synthesis via Hybrid Quantum-Classical Generative Model Architectures
di: Chen, Chi-Sheng, et al.
Pubblicazione: (2025)

Reinforcement learning framework for the mechanical design of microelectronic components under multiphysics constraints
di: Nair, Siddharth, et al.
Pubblicazione: (2025)

CrystalGRW: Generative Modeling of Crystal Structures with Targeted Properties via Geodesic Random Walks
di: Tangsongcharoen, Krit, et al.
Pubblicazione: (2025)

Jointly Reinforcing Diversity and Quality in Language Model Generations
di: Li, Tianjian, et al.
Pubblicazione: (2025)

Reweighted Flow Matching via Unbalanced OT for Label-free Long-tailed Generation
di: Song, Hyunsoo, et al.
Pubblicazione: (2025)

Generative Learning of the Solution of Parametric Partial Differential Equations Using Guided Diffusion Models and Virtual Observations
di: Gao, Han, et al.
Pubblicazione: (2024)

A Reinforcement Learning-Driven Transformer GAN for Molecular Generation
di: Li, Chen, et al.
Pubblicazione: (2025)

MolCryst-MLIPs: A Machine-Learned Interatomic Potentials Database for Molecular Crystals
di: Lahouari, Adam, et al.
Pubblicazione: (2026)

CrystalFramer: Rethinking the Role of Frames for SE(3)-Invariant Crystal Structure Modeling
di: Ito, Yusei, et al.
Pubblicazione: (2025)

Autonomous Discovery of the Ising Model's Critical Parameters with Reinforcement Learning
di: Man, Hai, et al.
Pubblicazione: (2026)

Shaping Laser Pulses with Reinforcement Learning
di: Capuano, Francesco, et al.
Pubblicazione: (2025)

OptPDE: Discovering Novel Integrable Systems via AI-Human Collaboration
di: Kantamneni, Subhash, et al.
Pubblicazione: (2024)

Geometric Deep Learning for Molecular Crystal Structure Prediction
di: Kilgour, Michael, et al.
Pubblicazione: (2023)

Generative Design of Crystal Structures by Point Cloud Representations and Diffusion Model
di: Li, Zhelin, et al.
Pubblicazione: (2024)

Generative Neural Operators through Diffusion Last Layer
di: Park, Sungwon, et al.
Pubblicazione: (2026)

Reinforcement Learning Closures for Underresolved Partial Differential Equations using Synthetic Data
di: Heimbach, Lothar, et al.
Pubblicazione: (2025)

A Model-Guided Neural Network Method for the Inverse Scattering Problem
di: Tsang, Olivia, et al.
Pubblicazione: (2025)

Modelling Gas-Phase Reaction Kinetics with Guided Particle Diffusion Sampling
di: Millard, Andrew, et al.
Pubblicazione: (2026)

Adaptive Uncertainty-Guided Model Selection for Data-Driven PDE Discovery
di: Thanasutives, Pongpisit, et al.
Pubblicazione: (2023)

Large Language Model-Enhanced Reinforcement Learning for Diverse and Novel Recommendations
di: Woo, Jiin, et al.
Pubblicazione: (2025)

Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization
di: Meyer, Nico, et al.
Pubblicazione: (2024)

Trading Devil RL: Backdoor attack via Stock market, Bayesian Optimization and Reinforcement Learning
di: Mengara, Orson
Pubblicazione: (2024)

Machine Learning Workflow for Analysis of High-Dimensional Order Parameter Space: A Case Study of Polymer Crystallization from Molecular Dynamics Simulations
di: Tourani, Elyar, et al.
Pubblicazione: (2025)

chemtrain: Learning Deep Potential Models via Automatic Differentiation and Statistical Physics
di: Fuchs, Paul, et al.
Pubblicazione: (2024)

Graph-Based Learning of Free Surface Dynamics in Generalized Newtonian Fluids using Smoothed Particle Hydrodynamics
di: Kim, Hyo-Jin, et al.
Pubblicazione: (2025)

Uncovering the Computational Roles of Nonlinearity in Sequence Modeling Using Almost-Linear RNNs
di: Brenner, Manuel, et al.
Pubblicazione: (2025)

CrystalFormer-CSP: Thinking Fast and Slow for Crystal Structure Prediction
di: Cao, Zhendong, et al.
Pubblicazione: (2025)

A Physics-Guided Probabilistic Surrogate Modeling Framework for Digital Twins of Underwater Radiated Noise
di: Deo, Indu Kant, et al.
Pubblicazione: (2025)

Meent: Differentiable Electromagnetic Simulator for Machine Learning
di: Kim, Yongha, et al.
Pubblicazione: (2024)

Scaling Quantum Machine Learning without Tricks: High-Resolution and Diverse Image Generation
di: Jäger, Jonas, et al.
Pubblicazione: (2026)

Plasma Shape Control via Zero-shot Generative Reinforcement Learning
di: Wu, Niannian, et al.
Pubblicazione: (2025)

Reinforcement Learning for Chemical Ordering in Alloy Nanoparticles
di: Elsborg, Jonas, et al.
Pubblicazione: (2025)

Estimating Reaction Barriers with Deep Reinforcement Learning
di: Pal, Adittya
Pubblicazione: (2024)

CrysToGraph: A Comprehensive Predictive Model for Crystal Materials Properties and the Benchmark
di: Wang, Hongyi, et al.
Pubblicazione: (2024)

Wyckoff Transformer: Generation of Symmetric Crystals
di: Kazeev, Nikita, et al.
Pubblicazione: (2025)