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Diversity

Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.

Papers

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Showing 6401–6425 of 9051 papers

TitleStatusHype
Scaling-up Disentanglement for Image TranslationCode1
High-Fidelity Pluralistic Image Completion with TransformersCode1
Feature Weighted Non-negative Matrix Factorization—0
Generating Novel Scene Compositions from Single Images and VideosCode1
Diversity Regularized Interests Modeling for Recommender Systems—0
Are all outliers alike? On Understanding the Diversity of Outliers for Detecting OODs—0
A News Recommender System Considering Temporal Dynamics and Diversity—0
Unsupervised Contextual Paraphrase Generation using Lexical Control and Reinforcement Learning—0
Seed banks can help to maintain the diversity of interacting phytoplankton speciesCode0
Complementary Evidence Identification in Open-Domain Question Answering—0
Multimodal Motion Prediction with Stacked TransformersCode1
Evaluating Post-Training Compression in GANs using Locality-Sensitive Hashing—0
Unsupervised Learning of Depth Estimation and Visual Odometry for Sparse Light Field Cameras—0
A Deep Neural Network Surrogate Modeling Benchmark for Temperature Field Prediction of Heat Source LayoutCode0
Local Patch AutoAugment with Multi-Agent CollaborationCode1
Attribute Alignment: Controlling Text Generation from Pre-trained Language ModelsCode0
Compacting Deep Neural Networks for Internet of Things: Methods and Applications—0
Efficient Subsampling of Realistic Images From GANs Conditional on a Class or a Continuous VariableCode0
Quality Evolvability ES: Evolving Individuals With a Distribution of Well Performing and Diverse OffspringCode0
DFS: A Diverse Feature Synthesis Model for Generalized Zero-Shot Learning—0
Beyond Trivial Counterfactual Explanations with Diverse Valuable ExplanationsCode1
Large Scale Image Completion via Co-Modulated Generative Adversarial NetworksCode1
Action detection using a neural network elucidates the genetics of mouse grooming behaviorCode1
Diversified Multiscale Graph Learning with Graph Self-Correction—0
Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition—0
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