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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 401–425 of 9051 papers

TitleStatusHype
Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label EnhancementCode1
Bacteriophage classification for assembled contigs using Graph Convolutional NetworkCode1
BalaGAN: Image Translation Between Imbalanced Domains via Cross-Modal TransferCode1
Balancing Diversity and Risk in LLM Sampling: How to Select Your Method and Parameter for Open-Ended Text GenerationCode1
DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific DeltaCode1
Deep Image Harmonization with Learnable AugmentationCode1
Deep Time Series Forecasting with Shape and Temporal CriteriaCode1
A Bayesian Flow Network Framework for Chemistry TasksCode1
AffordPose: A Large-scale Dataset of Hand-Object Interactions with Affordance-driven Hand PoseCode1
Deep Encoder-Decoder Networks for Classification of Hyperspectral and LiDAR DataCode1
DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery DetectionCode1
Deep Color Transfer using Histogram AnalogyCode1
Bayesian Adversarial Human Motion SynthesisCode1
Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problemCode1
Deep Diversity-Enhanced Feature Representation of Hyperspectral ImagesCode1
DeepFacePencil: Creating Face Images from Freehand SketchesCode1
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask LearningCode1
Synth-Empathy: Towards High-Quality Synthetic Empathy DataCode1
DGPO: Discovering Multiple Strategies with Diversity-Guided Policy OptimizationCode1
BeLFusion: Latent Diffusion for Behavior-Driven Human Motion PredictionCode1
Grounding Language to Autonomously-Acquired Skills via Goal GenerationCode1
Benchmarking Algorithms for Federated Domain GeneralizationCode1
Automatic Data Augmentation for 3D Medical Image SegmentationCode1
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from DataCode1
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower BoundsCode1
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