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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 4351–4400 of 9051 papers

TitleStatusHype
Diverse Human Motion Prediction Guided by Multi-Level Spatial-Temporal AnchorsCode1
Sample-efficient Multi-objective Molecular Optimization with GFlowNetsCode1
Why the Mansfield Rule can't work: a supply demand analysis—0
MMPD: Multi-Domain Mobile Video Physiology DatasetCode1
Cluster Index Modulation for Reconfigurable Intelligent Surface-Assisted mmWave Massive MIMO—0
Mask Conditional Synthetic Satellite ImageryCode1
Performative Recommendation: Diversifying Content via Strategic IncentivesCode0
A Vector Quantized Approach for Text to Speech Synthesis on Real-World Spontaneous SpeechCode2
Effective Data Augmentation With Diffusion ModelsCode2
Ethical Considerations for Responsible Data CurationCode0
Mind the Gap! Bridging Explainable Artificial Intelligence and Human Understanding with Luhmann's Functional Theory of Communication—0
Diversity is Definitely Needed: Improving Model-Agnostic Zero-shot Classification via Stable DiffusionCode1
Diverse Probabilistic Trajectory Forecasting with Admissibility ConstraintsCode0
DivBO: Diversity-aware CASH for Ensemble Learning—0
Coherence and Diversity through Noise: Self-Supervised Paraphrase Generation via Structure-Aware Denoising—0
LoFT: Enhancing Faithfulness and Diversity for Table-to-Text Generation via Logic Form ControlCode1
Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoy—0
This Intestine Does Not Exist: Multiscale Residual Variational Autoencoder for Realistic Wireless Capsule Endoscopy Image Generation—0
Diversity Induced Environment Design via Self-Play—0
Semantic-Guided Generative Image Augmentation Method with Diffusion Models for Image Classification—0
AdaptDiffuser: Diffusion Models as Adaptive Self-evolving PlannersCode1
ANTM: An Aligned Neural Topic Model for Exploring Evolving TopicsCode1
Combining Deep Neural Reranking and Unsupervised Extraction for Multi-Query Focused Summarization—0
Get3DHuman: Lifting StyleGAN-Human into a 3D Generative Model using Pixel-aligned Reconstruction Priors—0
Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition—0
adSformers: Personalization from Short-Term Sequences and Diversity of Representations in Etsy Ads—0
UW-CVGAN: UnderWater Image Enhancement with Capsules Vectors Quantization—0
Pathologies of Predictive Diversity in Deep Ensembles—0
Uncertain Quality-Diversity: Evaluation methodology and new methods for Quality-Diversity in Uncertain DomainsCode0
Evolving Flying Machines in Minecraft Using Quality DiversityCode1
An Out-of-Domain Synapse Detection Challenge for Microwasp Brain Connectomes—0
Structured mutation inspired by evolutionary theory enriches population performance and diversity—0
Does Deep Active Learning Work in the Wild?—0
Diverse legal case search—0
Sustainable Diversity of Phage-Bacteria Systems—0
ProtoSeg: Interpretable Semantic Segmentation with Prototypical PartsCode1
Informational Diversity and Affinity Bias in Team Growth Dynamics—0
Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines?Code0
Joint Training of Deep Ensembles Fails Due to Learner CollusionCode0
Variation-Aware Semantic Image Synthesis—0
Accelerate & Actualize: Can 2D Materials Bridge the Gap Between Neuromorphic Hardware and the Human Brain?—0
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation—0
Bipartite Graph Diffusion Model for Human Interaction GenerationCode0
NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning ProblemsCode0
Designing Data: Proactive Data Collection and Iteration for Machine Learning—0
Data Augmentation Alone Can Improve Adversarial TrainingCode1
Hatchery-produced sandfish (Holothuria scabra) show altered genetic diversity in New Caledonia—0
Towards NeuroAI: Introducing Neuronal Diversity into Artificial Neural Networks—0
ECGAN: Self-supervised generative adversarial network for electrocardiography—0
Representing Interlingual Meaning in Lexical Databases—0
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