repoGitLabTrust 82 · PrimaryPublished 28d agoLive · 9h ago
light-and-molecules/melts
Machine Learning for Excited State Dynamics. A reference machine learning implementation in the Newton-X/MLatom ecosystem.
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 56%Guiding generative models to uncover diverse and novel crystals via reinforcement learning →
- PossiblePossibly related (embedding) · 53%AI, Machine Learning and Deep Learning Advances in the Photothermal, Photoacoustic and Diffusion Wave Sciences and Technologies - AIP Publishing LLC →
- PossiblePossibly related (embedding) · 47%Machine learning maps the atomic complexity inside batteries - Nanowerk →
- PossiblePossibly related (embedding) · 51%Machine learning helps optimize energy storage at the atomic scale - Inspenet →
- PossiblePossibly related (embedding) · 54%Accelerating sustainable glass discovery: integrating molecular dynamics, machine learning, and robotic synthesis - Nature →
- PossiblePossibly related (embedding) · 56%Vibrational power spectra as a tool to benchmark universal machine-learning interatomic potentials for molecular systems: the OMOL-1k-MD data set - Nature →
Covers
Covers (incoming)
newsMachine learning maps the atomic complexity inside batteries - NanowerknewsMachine learning helps optimize energy storage at the atomic scale - InspenetnewsAccelerating sustainable glass discovery: integrating molecular dynamics, machine learning, and robotic synthesis - NaturenewsVibrational power spectra as a tool to benchmark universal machine-learning interatomic potentials for molecular systems: the OMOL-1k-MD data set - Nature
Related across the graph
newsMachine learning helps optimize energy storage at the atomic scale - InspenetnewsGuiding generative models to uncover diverse and novel crystals via reinforcement learningnewsVibrational power spectra as a tool to benchmark universal machine-learning interatomic potentials for molecular systems: the OMOL-1k-MD data set - NaturenewsMachine learning maps the atomic complexity inside batteries - NanowerknewsAI, Machine Learning and Deep Learning Advances in the Photothermal, Photoacoustic and Diffusion Wave Sciences and Technologies - AIP Publishing LLCnewsAccelerating sustainable glass discovery: integrating molecular dynamics, machine learning, and robotic synthesis - Nature