An intrinsic effective sample size for manifold MCMC is defined via kernel discrepancy as the number of independent draws yielding equivalent expected squared discrepancy to the target.
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Finite sequential binary data support practical boundary probabilities via reverse-martingale limits rather than exact degeneracy, with a three-condition stopping rule that separates transient from genuine cases.
RG-inspired lattice models for piecewise GLMs provide explicit interpretable partitions and a replica-analysis-derived scaling law for regularization that allows increasing complexity without expected rise in generalization loss.
Crowdsourced judgments reliably flag authentic videos but frequently miss manipulations and struggle to identify whether changes are audio-only, video-only, or both.
sumoITScontrol provides a collection of traffic controllers for SUMO simulations and stresses the importance of variance-aware evaluation methods for reproducible research.
citing papers explorer
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Intrinsic effective sample size for manifold-valued Markov chain Monte Carlo via kernel discrepancy
An intrinsic effective sample size for manifold MCMC is defined via kernel discrepancy as the number of independent draws yielding equivalent expected squared discrepancy to the target.
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Practical Boundary Degeneracy and Reverse-Martingale Limits in Sequential Binary Models
Finite sequential binary data support practical boundary probabilities via reverse-martingale limits rather than exact degeneracy, with a three-condition stopping rule that separates transient from genuine cases.
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A renormalization-group inspired lattice-based framework for piecewise generalized linear models
RG-inspired lattice models for piecewise GLMs provide explicit interpretable partitions and a replica-analysis-derived scaling law for regularization that allows increasing complexity without expected rise in generalization loss.
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Beyond Seeing Is Believing: On Crowdsourced Detection of Audiovisual Deepfakes
Crowdsourced judgments reliably flag authentic videos but frequently miss manipulations and struggle to identify whether changes are audio-only, video-only, or both.
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sumoITScontrol: Traffic Controller Collection for SUMO Traffic Simulations
sumoITScontrol provides a collection of traffic controllers for SUMO simulations and stresses the importance of variance-aware evaluation methods for reproducible research.