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Novelty Detection

Scientific Novelty Detection

Papers

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Showing 176–200 of 249 papers

TitleStatusHype
Neural Neighborhood Encoding for Classification—0
New Perspective on Progressive GANs Distillation for One-class Novelty Detection—0
NN-EVCLUS: Neural Network-based Evidential Clustering—0
Non-linear prediction with LSTM recurrent neural networks for acoustic novelty detection—0
Normalizing flows for novelty detection in industrial time series data—0
Normative Modeling of Neuroimaging Data using Scalable Multi-Task Gaussian Processes—0
NovAScore: A New Automated Metric for Evaluating Document Level Novelty—0
Novelty Detection and Learning from Extremely Weak Supervision—0
Novelty Detection: A Perspective from Natural Language Processing—0
Novelty Detection for Election Fraud: A Case Study with Agent-Based Simulation Data—0
Novelty Detection in MultiClass Scenarios with Incomplete Set of Class Labels—0
Novelty Detection in Network Traffic: Using Survival Analysis for Feature Identification—0
Novelty Detection in Time Series via Weak Innovations Representation: A Deep Learning Approach—0
Novelty Detection Meets Collider Physics—0
Novelty Detection Through Model-Based Characterization of Neural Networks—0
Self-supervised network distillation: an effective approach to exploration in sparse reward environmentsCode0
EX2: Exploration with Exemplar Models for Deep Reinforcement LearningCode0
Unsupervised Novelty Detection Methods Benchmarking with Wavelet DecompositionCode0
Multivariate Triangular Quantile Maps for Novelty DetectionCode0
Derandomized Novelty Detection with FDR Control via Conformal E-valuesCode0
Enhancing Multiple Reliability Measures via Nuisance-extended Information BottleneckCode0
TAP-DLND 1.0 : A Corpus for Document Level Novelty DetectionCode0
Generative Probabilistic Novelty Detection with Adversarial AutoencodersCode0
Neural Processes Mixed-Effect Models for Deep Normative Modeling of Clinical Neuroimaging DataCode0
AquaSignal: An Integrated Framework for Robust Underwater Acoustic AnalysisCode0
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