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Diversity

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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.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/collwe/JEDI-Crowd-Teaching

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Unlearn What You Have Learned: Adaptive Crowd Teaching with Exponentially Decayed Memory Learners

https://github.com/computationalmedia/supmmd

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SupMMD: A Sentence Importance Model for Extractive Summarization using Maximum Mean Discrepancy

https://github.com/compvis/fm-boosting

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Boosting Latent Diffusion with Flow Matching

https://github.com/coraliepicoche/brownian_bug_3d

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Local intraspecific aggregation in phytoplankton model communities: spatial scales of occurrence and implications for coexistence

https://github.com/corentin-ryr/multimedeval

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MultiMedEval: A Benchmark and a Toolkit for Evaluating Medical Vision-Language Models

https://github.com/corl-team/sdde

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Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy

https://github.com/corl-team/xland-minigrid

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XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX

https://github.com/cps11/catvrnn

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CatVRNN: Generating Category Texts via Multi-task Learning

https://github.com/cps11/darl

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Reinforcement Learning for Few-Shot Text Generation Adaptation

https://github.com/cpu9xx/ael

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When SparseMoE Meets Noisy Interactions: An Ensemble View on Denoising Recommendation

https://github.com/craftjarvis/mc-controller

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Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Prediction

https://github.com/craftjarvis/mcu

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Towards Evaluating Generalist Agents: An Automated Benchmark in Open World

https://github.com/cristal-3dsam/bigraphdiff

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Bipartite Graph Diffusion Model for Human Interaction Generation

https://github.com/critical88/boxgnn

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When Box Meets Graph Neural Network in Tag-aware Recommendation

https://github.com/croitorualin/dlcr

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DLCR: A Generative Data Expansion Framework via Diffusion for Clothes-Changing Person Re-ID

https://github.com/cs-giung/distill-latentbe

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Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation

https://github.com/csebuetnlp/banglaparaphrase

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BanglaParaphrase: A High-Quality Bangla Paraphrase Dataset

https://github.com/csguoh/adaptir

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Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-Experts

https://github.com/csubiogroup/pgmg

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PGMG: A Pharmacophore-Guided Deep Learning Approach for Bioactive Molecular Generation

https://github.com/cswin/AWC

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CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation

https://github.com/cuihaosabrina/ai-enhanced-collective-intelligence

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AI-enhanced Collective Intelligence

https://github.com/cuishuhao/BNM

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Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations

https://github.com/cuteythyme/q-diversity

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Modeling the Q-Diversity in a Min-max Play Game for Robust Optimization

https://github.com/cvblab/AI4SkIN_leaderboard

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Benchmarking histopathology foundation models in a multi-center dataset for skin cancer subtyping

https://github.com/cvdfoundation/google-landmark

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Two-stage Discriminative Re-ranking for Large-scale Landmark Retrieval

https://github.com/cvjena/ITAL

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Information-Theoretic Active Learning for Content-Based Image Retrieval

https://github.com/cvlab-epfl/adv_param_pose_prior

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Adversarial Parametric Pose Prior

https://github.com/cvlab-yonsei/MNAD

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Learning Memory-guided Normality for Anomaly Detection

https://github.com/cylumn/qd-generative-sampling

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Quality-Diversity Generative Sampling for Learning with Synthetic Data

https://github.com/cyp-jlu-ai/ba-lora

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BA-LoRA: Bias-Alleviating Low-Rank Adaptation to Mitigate Catastrophic Inheritance in Large Language Models

https://github.com/cyrilpic/radcomp

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DATED: Guidelines for Creating Synthetic Datasets for Engineering Design Applications

https://github.com/d1024choi/pathgan_pytorch

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PathGAN: Local Path Planning with Attentive Generative Adversarial Networks

https://github.com/daenuprobst/anon_aichem

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Social and environmental impact of recent developments in machine learning on biology and chemistry research

https://github.com/dalhousieai/benthicnet

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BenthicNet: A global compilation of seafloor images for deep learning applications

https://github.com/danjun6737/transface

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TransFace: Calibrating Transformer Training for Face Recognition from a Data-Centric Perspective

https://github.com/danmcduff/scampsdataset

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SCAMPS: Synthetics for Camera Measurement of Physiological Signals

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