Papers Density Estimation
“Density Estimation” 태그가 달린 논문 1,624편 · 필터 해제
GLASS: Graph-Language Alignment with Spherical Scoring for Transferable Graph-Level Anomaly Detection
We introduce GLASS, a framework for graph-level anomaly detection (GLAD) that achieves robust cross-domain transferability through graph-language alignment on the unit hypersphere. GLASS builds a unified representation s…
Density EstimationAnomaly DetectionPuTR-CouT: Counting-by-Tracking in Camera-Trap Image Sequences
Species identification in camera trap images has been widely studied, but key ecological modeling tasks such as species abundance or density estimation also require counting individual animals. However, the lack of count…
Density EstimationFaster Learning under Relaxed Local Differential Privacy
We consider density estimation under the relaxed local differential privacy condition that the privatized distributions are $α$-close in total variation distance. We show that adding independent noise with a convenient s…
Density EstimationHigh-dimensional nonparametric changepoint detection via low-rank degree-two density projection
Detecting distributional changes in high dimension is difficult when neither the pre-change nor post-change density is parametrically specified. We introduce a representation-based approach that retains all degree-at-mos…
Density EstimationBand-Count Dense Modal Estimation with Fixed-Frequency Differentiable Resonator Refinement
Task B of the 1st DAFx Parameter Estimation Challenge requires estimating the frequencies, decay rates, gains, and number of modes in a dense plate-reverb impulse response. Weak and overlapping modes make sparse peak det…
Density EstimationCompactly supported radial basis functions as probability density functions
Compactly Supported Radial Basis Functions (CS-RBFs) are a fundamental tool in multivariate approximation theory. However, their use in statistics and probability modeling remains underexplored, having been used mainly t…
Incremental LearningGaussian ProcessesDensity EstimationRe-thinking Mammography Transfer Learning: The Dataset-Informed Transfer Learning (DITL) Framework for Breast Cancer Screening and Lesion Diagnosis
Enhancing classification performance in mammography remains a persistent challenge across both small curated datasets and large-scale clinical cohorts. Conventional transfer learning approaches often neglect dataset-spec…
Density EstimationTransfer LearningPeTeR: Post-Training Robustification of Probabilistic Circuits
Probabilistic circuits (PCs) can model complex joint distributions while supporting exact and efficient computation of many inference queries. However, standard likelihood-based PC learning is vulnerable to overfitting a…
Density EstimationDistributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation
Missing values undermine statistical inference and machine learning pipelines, yet most imputation methods rely on heuristics or restrictive parametric assumptions that ignore the joint data distribution. We recast imput…
Density EstimationStabilized Higher-Order Influence Functions: Statistical Theory of a Class of Bilinear Forms
Higher-order influence functions, introduced in a series of articles (Robins et al., 2008, 2009a; van der Vaart, 2014; Robins et al., 2016, 2023; Liu et al., 2017), are a unified framework for constructing rate-optimal p…
Density EstimationBandwidth Selection in Kernel Density Estimation for Model Calibration
As deep learning models are increasingly deployed in high-stakes applications, providing well-calibrated uncertainty estimates has become as critical as achieving high predictive accuracy. While Kernel Density Estimation…
Density EstimationInformation Terra: A Narrative-Anchored Semantic-First Projection of Document Embeddings
We introduce Information Terra, a narrative-anchored semantic-first projection that places a document corpus on an Earth-like globe whose poles are two user-chosen endpoint documents and whose prime meridian is the great…
Density EstimationPhysics-informed Conditional Normalizing Flows for Angles-only Cislunar Orbit Determination
Generative Astrodynamics is advanced in this work by extending generative modelling to an orbit determination problem in the cislunar environment. The task is formulated as conditional density estimation, aiming to infer…
Density EstimationRGLD: Randomized Global-Local Density Estimation for Tabular Anomaly Detection
Unsupervised tabular anomaly detection requires methods that are accurate, robust across heterogeneous datasets, and computationally efficient. Classical statistical detectors are often efficient, but they usually rely o…
Density EstimationAnomaly DetectionDeCoFlow: Structural Decomposition of Normalizing Flows for Continual Anomaly Detection
In industrial environments, new product categories arrive sequentially, requiring continual anomaly detection without access to past data. Normalizing Flows (NFs) provide exact density estimation but suffer from catastro…
Density EstimationAnomaly DetectionMIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation
Normalizing Flows (NFs) are powerful generative models capable of exact density estimation and sampling. However, their strict invertibility often forces the model to exhaust its capacity on low-level pixel details, hind…
Representation LearningDensity EstimationImage GenerationKnowledge Cascade: Reverse Knowledge Distillation on Nonparametric Multivariate Functional Estimation
As machine learning models and datasets continue to grow, developing complex models has become increasingly computationally demanding. Knowledge distillation reduces deployment cost by compressing a large, well-trained t…
Knowledge DistillationDensity EstimationInformation-Theoretic Classifier-Free Guidance with Adaptive Schedule Optimization
Diffusion models have achieved strong performance in image, text-to-image, and video generation, where conditional generation is often controlled by classifier-free guidance (CFG). CFG improves condition consistency by i…
Density EstimationVideo GenerationCounting Trees from Satellite Imagery with Noisy Supervision
Counting individual trees is a fundamental task for environmental monitoring, yet remains largely unexplored with satellite imagery. At these resolutions, isolated trees may still be identifiable, but crown boundaries be…
Density EstimationA homotopy-type-theoretic generalization of neurosymbolic inference
A wide range of neurosymbolic (NeSy) systems compute one functional: a belief-weighted sum of a logical quantity over a space of $σ$-structures, of which weighted model counting, fuzzy logic, and probabilistic logic are …
Density Estimation