Copertina

Ubiquitous Symmetry at Critical Points Across Diverse Optimization Landscapes

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Schneider, Irmi
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence Atomic Physics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Accelerating Atomic Fine Structure Determination with Graph Reinforcement Learning
di: Ding, M., et al.
Pubblicazione: (2025)

Teaching Molecular Dynamics to a Non-Autoregressive Ionic Transport Predictor
di: Kim, Jiyeon, et al.
Pubblicazione: (2026)

Pulse Shape Discrimination Algorithms: Survey and Benchmark
di: Liu, Haoran, et al.
Pubblicazione: (2025)

Precision Spectroscopy of Fast, Hot Exotic Isotopes Using Machine Learning Assisted Event-by-Event Doppler Correction
di: Udrescu, Silviu-Marian, et al.
Pubblicazione: (2023)

A large language model-type architecture for high-dimensional molecular potential energy surfaces
di: Zhu, Xiao, et al.
Pubblicazione: (2024)

Crystal Generation using the Fully Differentiable Pipeline and Latent Space Optimization
di: Ridwan, Osman Goni, et al.
Pubblicazione: (2026)

A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction
di: Yan, Keqiang, et al.
Pubblicazione: (2024)

Review and experimental benchmarking of machine learning algorithms for efficient optimization of cold atom experiments
di: Anton, Oliver, et al.
Pubblicazione: (2023)

A Comprehensive Benchmarking Platform for Deep Generative Models in Molecular Design
di: Singh, Adarsh
Pubblicazione: (2025)

Data-Efficient Machine Learning Potentials via Difference Vectors Based on Local Atomic Environments
di: Shao, Xuqiang, et al.
Pubblicazione: (2025)

Soft Checksums to Flag Untrustworthy Machine Learning Surrogate Predictions and Application to Atomic Physics Simulations
di: Lauer, Casey, et al.
Pubblicazione: (2024)

LLM-based Multi-Agent Copilot for Quantum Sensor
di: Sha, Rong, et al.
Pubblicazione: (2025)

Solving tricky quantum optics problems with assistance from (artificial) intelligence
di: Pandey, Manas, et al.
Pubblicazione: (2025)

Learning spatially structured open quantum dynamics with regional-attention transformers
di: Du, Dounan, et al.
Pubblicazione: (2025)

MV-CLAM: Multi-View Molecular Interpretation with Cross-Modal Projection via Language Model
di: Ha, Sumin, et al.
Pubblicazione: (2025)

Symmetry Breaking in Neural Network Optimization: Insights from Input Dimension Expansion
di: Zhang, Jun-Jie, et al.
Pubblicazione: (2024)

Metric Rarity and the Emergence of Symmetry in G-Invariant Potential Surfaces
di: Schneider, Irmi
Pubblicazione: (2026)

A Tale of Two Symmetries: Exploring the Loss Landscape of Equivariant Models
di: Xie, YuQing, et al.
Pubblicazione: (2025)

Diversity-Enriched Option-Critic
di: Kamat, Anand, et al.
Pubblicazione: (2020)

Fractal Landscapes in Policy Optimization
di: Wang, Tao, et al.
Pubblicazione: (2023)

Predictions of charge density distributions for nuclei with $Z \geq 8$
di: Wang, Yun Dong, et al.
Pubblicazione: (2026)

A Cross-Domain Graph Learning Protocol for Single-Step Molecular Geometry Refinement
di: Liu, Chengchun, et al.
Pubblicazione: (2026)

Quality-Diversity Actor-Critic: Learning High-Performing and Diverse Behaviors via Value and Successor Features Critics
di: Grillotti, Luca, et al.
Pubblicazione: (2024)

AlphaLab: Autonomous Multi-Agent Research Across Optimization Domains with Frontier LLMs
di: Hogan, Brendan R., et al.
Pubblicazione: (2026)

Can machine learning for quantum-gas experiments be explainable?
di: Zwolak, I. B. Spielman amd J. P.
Pubblicazione: (2026)

The Role of Symmetry in Optimizing Overparameterized Networks
di: Sareen, Kusha, et al.
Pubblicazione: (2026)

Optical Memory Optimization Across Rubidium Isotopes and Transitions
di: Danielov, T., et al.
Pubblicazione: (2026)

Robust Model-Based Optimization for Challenging Fitness Landscapes
di: Ghaffari, Saba, et al.
Pubblicazione: (2023)

Scaling Laws and Symmetry, Evidence from Neural Force Fields
di: Ngo, Khang, et al.
Pubblicazione: (2025)

Generative Inverse Design: From Single Point Optimization to a Diverse Design Portfolio via Conditional Variational Autoencoders
di: Zamrai, Muhammad Arif Hakimi
Pubblicazione: (2025)

Matrix Sensing with Kernel Optimal Loss: Robustness and Optimization Landscape
di: Song, Xinyuan, et al.
Pubblicazione: (2025)

A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
di: Shmuel, Assaf, et al.
Pubblicazione: (2024)

Ethical Fairness in Ubiquitous Health Sensing without Known Attributes
di: Roy, Shaily, et al.
Pubblicazione: (2026)

Continual Optimization with Symmetry Teleportation for Multi-Task Learning
di: Zhou, Zhipeng, et al.
Pubblicazione: (2025)

Remove Symmetries to Control Model Expressivity and Improve Optimization
di: Ziyin, Liu, et al.
Pubblicazione: (2024)

AI Methods for Permutation Circuit Synthesis Across Generic Topologies
di: Villar, Victor, et al.
Pubblicazione: (2025)

Adapting Critic Match Loss Landscape Visualization to Off-policy Reinforcement Learning
di: Liu, Jingyi, et al.
Pubblicazione: (2026)

Decoding the Diversity: A Review of the Indic AI Research Landscape
di: KJ, Sankalp, et al.
Pubblicazione: (2024)

AIM: Adaptive Intervention for Deep Multi-task Learning of Molecular Properties
di: Minot, Mason, et al.
Pubblicazione: (2025)

Artificial Intelligence for Direct Prediction of Molecular Dynamics Across Chemical Space
di: Ge, Fuchun, et al.
Pubblicazione: (2025)