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3,686 papers
CatSIM uses a structural similarity image quality paradigm and is robust to small perturbations in location so that structures in similar, but not entirely overlapping, regions of two images are rated higher than using simple matching.
DeepX‐GAN (Dependence‐Enhanced Embedding for Physical eXtremes—Generative Adversarial Network) is introduced, a deep generative model that explicitly captures the spatial structure of rare extremes and enables the simulation of statistically plausible extremes beyond the observed record, evaluated against long climate...
A growing trend involves integrating human knowledge into learning frameworks, leveraging subtle human feedback to refine AI models. While these approaches have shown promising results in practice, the theoretical understanding of when and why such approaches are effective remains limited. This work takes steps toward...
The Anchored Extra-Proximal (AEP) framework is introduced, which combines an anchored extrapolation step with an inexact anchored proximal update satisfying a relative-error condition to recover the composite Fast Extragradient method in the first-order setting.
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Matrix completion, the problem of estimating missing entries in a matrix from noisily observed ones, underlies a diverse array of problems such as recommender systems and counterfactual outcome estimation in panel data. Many algorithms address the problem using regularized least squares, often with the nuclear norm as...
A central goal when designing treatment policies is often to"do no harm", that is, to avoid interventions that improve average outcomes while worsening outcomes for some individuals. A widely used notion for harm is the fraction of negatively affected (FNA), defined as the probability that an intervention decreases an...
Clipping improves robustness in both studies, with gains varying across detectors and contamination settings, and at a target false-positive rate, clipping improves the log-likelihood--log-rank ratio detector's true-positive rate.
Worst-case Optimal Recovery (OR) and Bayesian learning describe the same Gaussian-quadratic-Hilbert problems in two vocabularies. We sharpen the correspondence - the radius of information equals a nugget-optimized GP posterior variance and is attained by the posterior mean at a closed-form balance nugget - and measure,...
A variational formulation inspired by empirical risk minimization subject to relative entropy regularization (ERM-RER) is proposed using a variational formulation inspired by empirical risk minimization subject to relative entropy regularization to guarantee exact unlearning for Gibbs supervised learning algorithms.
Flow-Based Distribution Matching is introduced, a non-adversarial framework that learns this reference-directed geometry through spherical conditional velocity regression that achieves performance nearly on par with DM and remains competitive with existing SSL methods.
Selective classification enables a model to abstain from predictions on uncertain instances, but existing approaches typically reject them through confidence scores, predefined coverage constraints or instance-level distance measures. These approaches may overlook the collective geometric structure of difficult samples...
It is proved that the estimated conditional distributions converge in energy distance to the true ones, which implies that the learned representation is asymptotically sufficient.
A machine-learning approach called CheMeleon provides a practical way to develop new drugs or other molecules with much less detailed, expensive experimentation.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Health & Bioscience
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Data Mining & Modeling
GPT-Lab
· gpt-lab.eu
Nov 3, 2026
Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.
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