PWO is a trust-region optimizer for autoregressive NQS that improves stability over Adam and stochastic reconfiguration methods while scaling to 1.5B-parameter models on spin systems.
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Biometrika , year = 1970, month = apr, volume =
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HST/WFC3 UV imaging of SR 12 c measures accretion luminosity of 1.65 ± 0.19 × 10^{-5} L_⊙ and rate of 8 ± 2 × 10^{-12} M_⊙ yr^{-1}, placing it at the end stages of giant planet assembly with a full UV-to-sub-mm SED.
Uncorrected Gaussian residual penalties in full-space sampling converge after marginalization to the graph-lifted reduced posterior multiplied by the inverse absolute determinant of the state Jacobian, requiring explicit determinant corrections for equivalence.
A homotopy-plus-MCMC data-generation pipeline trains a mass-conditioned diffusion model that yields 40% more feasible initial costates and a better Pareto front for multiobjective indirect low-thrust transfers than adjoint-control-transformation baselines.
LATTE coordinates LLM agent teams with an evolving shared task graph, cutting token use, time, and failures while matching or beating accuracy of MetaGPT, leader-worker, and static methods.
Two long period radio transients are detached white dwarf-M dwarf binaries with matching periods, massive cool crystallized white dwarfs, low inclinations, and an estimated population of 100-2000 such systems within 2 kpc.
Reactive graphs enable efficient MCMC inference in probabilistic programming languages by automatically tracking and selectively recomputing data dependencies during sampling.
A hierarchical Bayesian framework pools information across sparse dynamical system datasets via a shared population distribution to improve parameter inference and prediction over unpooled approaches.
LLM embeddings condition a generative transformer to enable faster convergence, better performance, and generalization to unseen LHC processes using a single model.
Latent diffusion model parameterization allows MCMC and SMC to outperform latent-space ESMDA in data mismatch and uncertainty reduction for 3D subsurface DA, while model-space ESMDA produces unrealistic posteriors.
MCMC analysis of 1965-2024 energy data yields a 2.01% growth rate, falsifying Kardashev's 1%, and shows no realistic trajectory reaches Type II, motivating a new information-energy metric (KarNak).
dynesty is an open-source Python package for dynamic nested sampling that improves efficiency in Bayesian posterior and evidence estimation compared to MCMC on certain problems.
The chirp-mass distribution of GW-detected binary black holes shows a ladder of peaks doubling in mass, with a new intermediate peak at 19 solar masses confirming a prior prediction from the hierarchical merger model.
U-turn chains are Markov chains formed by short forward-backward diffusion steps that remain on the learned manifold and, with Metropolis-Hastings, sample from energy-modified targets, exhibiting an ergodicity-breaking transition on fragmented manifolds.
Theoretical analysis of multiproposal MCMC in the infinite proposal limit using involutive theory yields new methods and inter-method relationships.
JADES DR5 delivers a public catalog of Bayesian-inferred stellar masses, SFRs, SFHs, dust, metallicities, and AGN contributions for ~500k galaxies via Prospector with an evolving SFMS prior.
Validates redshift-space power spectrum and bispectrum analysis on Abacus-PNG mocks to recover unbiased f_NL constraints for Euclid spectroscopic sample.
Deep learning infers Δν and ν_max from one-month TESS and K2 observations of red giants with reliable results for ~50% of Kepler/K2 samples and ~23% of TESS stars, plus ΔΠ1 for ~200 K2 young red giants that match known patterns.
Extends KMS-detailed balance constructions from open quantum systems to prepare microcanonical ensembles and other stationary states with criteria for efficient implementation.
GP15 maps BBH spectrograms to parameter posteriors via residual networks and normalizing flows, producing results consistent with LVK analyses on GWTC-2.1 and GWTC-3 events while running in seconds.
A multimodal GNN ablation for Nordic precipitation nowcasting shows sparse point observations improve station and onset scores while NWP and CRPS losses improve radar-grid performance, indicating local and field skills are distinct targets.
A quantum-inspired framework using effective Hamiltonians, Metropolis annealing and stochastic tensor-network compression is proposed for adaptive multi-demand routing in large-scale QKD networks.
Discovery of an eclipsing neutron star LMXB with clocked bursts, orbital period 6.483 hr, companion mass 0.6-0.8 Msun, and helium burst indications from energy ratio 120-130.
Bayesian ensemble MCMC fits a cubic-plus-damped-oscillatory model to Ghana malaria data, reports R² > 0.995, and extrapolates rising case counts through 2026 with widening uncertainty.
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