A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Matthias Zwicker, Hanspeter Pfister, Jeroen van Baar, et al.
EWA splatting introduces a resampling filter framework using elliptical Gaussian kernels for high-quality, alias-free rendering of volume and point-sampled surface data.
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Introduces RAS, a training-free sampling strategy for Diffusion Transformers that dynamically adjusts token updates based on region-adaptive criteria.
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SelfCheckGPT is a zero-resource, black-box hallucination detection method for generative LLMs that uses sampling-based consistency checking.
Bohan Li, Yutai Hou, Wanxiang Che
This survey categorizes data augmentation methods in NLP into paraphrasing, noising, and sampling based on the diversity of augmented data, and reviews their applications and challenges.
L. Yang, Zhilong Zhang, Yang Song, et al.
A comprehensive survey of diffusion models, categorizing research into efficient sampling, improved likelihood estimation, and handling special data structures, with a review of applications across domains.
Debottam Dutta, Jaehoon Hahm, Jianchong Chen, et al.
TILT is a training-free framework that improves compositional text-to-image generation by using a model-intrinsic reward to guide diffusion sampling toward joint concept presence.
Rahul Raguram, Ondřej Chum, Marc Pollefeys, et al.
USAC extends RANSAC with a universal framework integrating advanced sampling, verification, and model refinement for robust estimation.
Zhisheng Hu, Minghui Zhu, Peng Liu
Proposes an adaptive cyber defense using learning-based POMDP with Thompson sampling to counter multi-stage attacks under unknown exploit likelihoods and impacts.
Luming Zhang, Mingli Song, Qi Zhao, et al.
This paper introduces graphlets (small connected subgraphs) to represent aesthetic features and proposes a probabilistic model for automatic photo cropping via Gibbs sampling.
John Skilling
Nested sampling directly estimates the evidence by integrating likelihood over prior mass, with posterior samples as a by-product, and handles phase-change problems that defeat thermal annealing.
Maarten Blaauw, J. Andrés Christen
Introduces Bacon, a Bayesian autoregressive gamma process for flexible paleoclimate age-depth modeling with robust MCMC sampling.
Aayush Karan, Yilun Du
Proposes a simple iterative sampling algorithm that elicits reasoning from base LLMs at inference time, matching or outperforming RL post-training on single-shot tasks without additional training or verifiers.