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Machine Learning Science and Technology

  • h-index: 49
  • Total citations: 10,309
  • Total papers: 402
  • Impact factor: 4.124579124579125

Homepage: https://iopscience.iop.org/journal/2632-2153

Machine Learning Science and Technology

Journal
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H-Index = 49
Citations = 10.31K+

Papers

Evidence

Recent papers in Machine Learning Science and Technology

  1. Adaptive neural quantum states: a recurrent neural network perspectiveMachine Learning Science and Technology · Tue,
  2. AMD Versal AI-Engines for fixed latency environmentsMachine Learning Science and Technology · Fri,
  3. QuantumCanvas: a multimodal benchmark for learning two-body quantum interactionsMachine Learning Science and Technology · Thu,
  4. Bayesian Neural Networks versus deep ensembles for uncertainty quantification in machine learning interatomic potentialsMachine Learning Science and Technology · Mon,
  5. Text-trained LLMs can zero-shot extrapolate PDE dynamics, revealing a three-stage in-context learning mechanismMachine Learning Science and Technology · Thu,
  6. Pure and physics-guided deep learning approaches for spatio-temporal groundwater level predictionMachine Learning Science and Technology · Mon,
  7. PQuantML: a tool for end-to-end hardware-aware model compressionMachine Learning Science and Technology · Tue,
  8. Scalable autoregressive deep surrogates for complex microstructure dynamicsMachine Learning Science and Technology · Sat,
  9. Efficient identification of critical regions via flow matching-based Monte Carlo initializationMachine Learning Science and Technology · Sat,
  10. A Three-Head Hamiltonian-consistent neural network for nonadiabatic time-dependent density functional theory dynamicsMachine Learning Science and Technology · Sat,

About Machine Learning Science and Technology

Machine Learning Science and Technology carries 402 indexed papers, 10,309 citations, h-index 49 in Synapse's enriched corpus. Each paper indexed here includes structured clinical evidence extraction (PICO), methodology classification with level of evidence, and links to related guideline recommendations where applicable.

On Synapse's credibility score (derived from SJR ranking and cross-citation patterns), Machine Learning Science and Technology sits among the highest-credibility cardiovascular journals.

The journal's official homepage is at https://iopscience.iop.org/journal/2632-2153.

Use the feed below to follow new Machine Learning Science and Technology publications with AI-enriched analysis — each paper is decomposed into study design, population, intervention, comparator, primary outcome, and key finding, with the underlying evidence traceable to the primary source.

Deterministic synthesis from Synapse's enriched records — 111 words.