ciwGAN and fiwGAN models trained on isolated words spontaneously generate concatenated multi-word outputs and display early compositionality precursors.
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Equity and nontradable factors suffice to price corporate bond risk premia after Treasury term-structure adjustment, and a Bayesian model-averaging SDF that combines dozens of factors delivers out-of-sample Sharpe ratios of 1.5-1.8 while tracking the business cycle.
Proposes a cyclic 2.5D perceptual loss with manufacturer SUVR standardization for T1w MRI to tau PET synthesis, reporting improved regional agreement on ADNI and SCAN cohorts across U-Net, UNETR, SwinUNETR, CycleGAN, and Pix2Pix.
Sobolev regularization on the velocity and acceleration of centered log-ratio warps enables robust, monotonic pairwise functional data alignment without derivative computation.
A hybrid INLA-RF framework integrates Bayesian spatio-temporal modeling with random forests through two iterative algorithms to improve predictions and uncertainty quantification for environmental data.
Proposes Mallows-type weights for parameter-transfer learning that are asymptotically optimal for target prediction risk and selectively weight informative sources without requiring correct source models.
Thermally stable regional inversion lenses below the Pacific and Africa survive strong chemical buoyancy in thermochemical core simulations, and light elements accumulate near the poles to form chemically stable layers.
A framework using language models to simulate non-existent experiments and derive novel testable hypotheses on dative verb acquisition and cross-structural generalization in children.
Insertional code-switching in Chinese-English text and speech is not purely speaker-driven, since secondary-language productions are less predictable than primary-language alternatives.
A network growth model using opportunistic attachment via PageRank produces rich node dynamics, path-dependence, and a degenerate structure, suggested as a model for entrepreneurial growth with unbounded opportunities.
A registration-based supervoxel correlation pipeline applied to 1388 SCAPIS CCTA scans identifies age-associated cardiac changes outside common sub-regions with notable sex differences.
Hierarchical Bayesian and ML analysis of magnetar observables finds no statistically significant need for a distinct white-dwarf magnetar population.
Ohmic dissipation damps Slichter modes over 3-16 years, allowing persistence long enough that non-detection implies weak excitation rather than fast damping.
A new constructive heuristic for spontaneous volunteer assignment and scheduling in disasters approximates optimal primary objectives with a median 28x runtime speedup over exact solvers on large simulated instances.
Under conditional calibration, a latent group effect is identified as a closed-form ratio of the residual covariance of the signed score with the outcome to twice the residual score variance.
A column-and-constraint generation method with problem-specific outer approximation solves robust AC unit commitment under discrete hurricane line-outage scenarios faster than Gurobi on 200-bus instances and cuts unserved energy.
Upper bounds are derived showing that neural oscillator approximation errors for causal operators and stable second-order dynamical systems scale polynomially with the reciprocals of the widths of the two MLPs.
Multiple agents learn a consistent Koopman operator approximation for unknown nonlinear dynamics by performing local lifted-data estimation and achieving exponential consensus over a communication graph.
Ensemble feature selection on in-field hyperspectral data identifies compact spectral bands that enable nitrogen prediction in grapevine leaves and canopies with R² up to 0.82 at leaf level and transferable performance across scales and cultivars.
A comparative review with experiments identifying optimal preprocessing, models, and transfer strategies for large-scale pixel-wise crop mapping using Landsat 8 data across five sites.
Unity simulation of vehicle visibility from pedestrian viewpoints identifies wheels, front fenders, and headlights as most exposed and recommends eHMI placement on windshield, fenders, or side mirrors.
uGMRT Band-4 data on 3C48 show ionospheric phase structure functions with power-law turbulence, diffractive scales of 6.7-8.3 km, and anisotropy consistent with MSTIDs at ~19°N latitude.
ASTRO integrates GNNs with DQN for adaptive threshold optimization in anomaly detection, reporting F1 scores of 0.990 on SWaT and 0.788 on WADI datasets.
Random feature selection outperforms many state-of-the-art unsupervised feature selection methods on standard performance and efficiency metrics.
citing papers explorer
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Basic syntax from speech: Spontaneous concatenation in unsupervised deep neural networks
ciwGAN and fiwGAN models trained on isolated words spontaneously generate concatenated multi-word outputs and display early compositionality precursors.
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The Co-Pricing Factor Zoo
Equity and nontradable factors suffice to price corporate bond risk premia after Treasury term-structure adjustment, and a Bayesian model-averaging SDF that combines dozens of factors delivers out-of-sample Sharpe ratios of 1.5-1.8 while tracking the business cycle.
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Cyclic 2.5D Perceptual Loss for Cross-Modal 3D Medical Image Synthesis: T1w MRI to Tau PET
Proposes a cyclic 2.5D perceptual loss with manufacturer SUVR standardization for T1w MRI to tau PET synthesis, reporting improved regional agreement on ADNI and SCAN cohorts across U-Net, UNETR, SwinUNETR, CycleGAN, and Pix2Pix.
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Sobolev-Regularized Objective Functions for Robust Pairwise Alignment of Functional Data
Sobolev regularization on the velocity and acceleration of centered log-ratio warps enables robust, monotonic pairwise functional data alignment without derivative computation.
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INLA-RF: A Hybrid Modeling Strategy for Spatio-Temporal Environmental Data
A hybrid INLA-RF framework integrates Bayesian spatio-temporal modeling with random forests through two iterative algorithms to improve predictions and uncertainty quantification for environmental data.
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Generalized optimal parameter-transfer learning through Mallows-type model averaging
Proposes Mallows-type weights for parameter-transfer learning that are asymptotically optimal for target prediction risk and selectively weight informative sources without requiring correct source models.
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Thermochemical models of outer core convection with heterogeneous core-mantle boundary heat flux
Thermally stable regional inversion lenses below the Pacific and Africa survive strong chemical buoyancy in thermochemical core simulations, and light elements accumulate near the poles to form chemically stable layers.
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A systematic framework for generating novel experimental hypotheses from language models
A framework using language models to simulate non-existent experiments and derive novel testable hypotheses on dative verb acquisition and cross-structural generalization in children.
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Code-switching in text and speech challenges information-theoretic speaker design
Insertional code-switching in Chinese-English text and speech is not purely speaker-driven, since secondary-language productions are less predictable than primary-language alternatives.
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Network growth under opportunistic attachment
A network growth model using opportunistic attachment via PageRank produces rich node dynamics, path-dependence, and a degenerate structure, suggested as a model for entrepreneurial growth with unbounded opportunities.
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A method for supervoxel-wise association studies of age and other non-imaging variables from coronary computed tomography angiograms
A registration-based supervoxel correlation pipeline applied to 1388 SCAPIS CCTA scans identifies age-associated cardiac changes outside common sub-regions with notable sex differences.
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Data-Driven Constraints on Magnetar Population: No Evidence for a Distinct White Dwarf Channel
Hierarchical Bayesian and ML analysis of magnetar observables finds no statistically significant need for a distinct white-dwarf magnetar population.
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Ohmic and viscous damping of inner core translational oscillations
Ohmic dissipation damps Slichter modes over 3-16 years, allowing persistence long enough that non-detection implies weak excitation rather than fast damping.
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A priority-driven constructive heuristic for assigning and scheduling spontaneous volunteers in disaster response
A new constructive heuristic for spontaneous volunteer assignment and scheduling in disasters approximates optimal primary objectives with a median 28x runtime speedup over exact solvers on large simulated instances.
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Identification of Latent Group Effects under Conditional Calibration
Under conditional calibration, a latent group effect is identified as a closed-form ratio of the residual covariance of the signed score with the outcome to twice the residual score variance.
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Scheduling Electricity Production Units to Mitigate Severe Weather Impact: An Efficient Computational Implementation
A column-and-constraint generation method with problem-specific outer approximation solves robust AC unit commitment under discrete hurricane line-outage scenarios faster than Gurobi on 200-bus instances and cuts unserved energy.
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Upper Approximation Bounds for Neural Oscillators
Upper bounds are derived showing that neural oscillator approximation errors for causal operators and stable second-order dynamical systems scale polynomially with the reciprocals of the widths of the two MLPs.
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Distributed Koopman Operator Learning from Sequential Observations
Multiple agents learn a consistent Koopman operator approximation for unknown nonlinear dynamics by performing local lifted-data estimation and achieving exponential consensus over a communication graph.
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Integrating Feature Selection and Machine Learning for Nitrogen Assessment in Grapevine Leaves using In-Field Hyperspectral Imaging
Ensemble feature selection on in-field hyperspectral data identifies compact spectral bands that enable nitrogen prediction in grapevine leaves and canopies with R² up to 0.82 at leaf level and transferable performance across scales and cultivars.
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From Time-series Generation, Model Selection to Transfer Learning: A Comparative Review of Pixel-wise Approaches for Large-scale Crop Mapping
A comparative review with experiments identifying optimal preprocessing, models, and transfer strategies for large-scale pixel-wise crop mapping using Landsat 8 data across five sites.
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Analytical Study on the Exposedness of Potential Positions for External Human-Machine Interfaces
Unity simulation of vehicle visibility from pedestrian viewpoints identifies wheels, front fenders, and headlights as most exposed and recommends eHMI placement on windshield, fenders, or side mirrors.
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Studying Ionospheric Phase Structure Functions Using Wide-Band uGMRT (Band-4) Interferometric Data
uGMRT Band-4 data on 3C48 show ionospheric phase structure functions with power-law turbulence, diffractive scales of 6.7-8.3 km, and anisotropy consistent with MSTIDs at ~19°N latitude.
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ASTRO: Adaptive Spatio-Temporal Reinforcement Optimization for GNN Powered Anomly Detection in Cyber Physical Systems
ASTRO integrates GNNs with DQN for adaptive threshold optimization in anomaly detection, reporting F1 scores of 0.990 on SWaT and 0.788 on WADI datasets.
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Worse than Random: The Importance of a Baseline for Unsupervised Feature Selection
Random feature selection outperforms many state-of-the-art unsupervised feature selection methods on standard performance and efficiency metrics.
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Recommendations for Efficient and Responsible LLM Adoption within Industrial Software Development
A multi-case study plus survey produces seven actionable recommendations for efficient and responsible LLM use in industrial software engineering.
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LStein: A new approach to visualizing sparse 2.5-dimensional data
LStein is presented as a novel visualization approach for sparse 2.5-dimensional data, implemented in Python and demonstrated on astronomical lightcurves.
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Dark energy, spatial curvature, and star formation efficiency from JWST photometric and spectroscopic high-redshift galaxies
Bayesian joint constraints show that elevated star formation efficiency accounts for JWST high-z galaxy excess in flat Lambda CDM, without requiring deviations in dark energy equation of state or curvature.
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Matter-free gravitational collapse and the equivalence principle
Using an extended equivalence principle on the Klinkhamer metric, the radial dynamics of a degenerate wormhole reduce to test-particle fall in Schwarzschild spacetime, proving collapse of bound traversable states into Einstein-Rosen wormholes with a long lifetime estimate.
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Multi-sectoral Impacts of H2 and Synthetic Fuels Adoption for Heavy-duty Transportation Decarbonization
Scenario modeling shows hydrogen HDVs lower system costs and fossil demand but may raise natural gas use, while synthetic fuels increase DAC needs and total costs, with CO2 storage availability determining feasibility.
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Nonlinear Transformations Against Unlearnable Datasets
Nonlinear transformations enable DNNs to achieve substantial test accuracy gains (0.34% to 249.59%) on unlearnable CIFAR10 datasets from twelve protection methods, outperforming a recent linear baseline.