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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/DmitryUlyanov/texture_nets

공식 코드

Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesis

https://github.com/Dong-JinKim/DenseRelationalCaptioning

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Dense Relational Captioning: Triple-Stream Networks for Relationship-Based Captioning

https://github.com/DreadPiratePsyopus/Fine_Grained_Clf

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Fine-grained Image Classification and Retrieval by Combining Visual and Locally Pooled Textual Features

https://github.com/Droliven/DHMP_jittor

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Diverse Human Motion Prediction via Gumbel-Softmax Sampling from an Auxiliary Space

https://github.com/EAiler/comp-iv

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Instrumental Variable Estimation for Compositional Treatments

https://github.com/ENSTA-U2IS-AI/torch-uncertainty

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Packed-Ensembles for Efficient Uncertainty Estimation

https://github.com/EagleW/Multimedia-Generative-Script-Learning-for-Task-Planning

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Multimedia Generative Script Learning for Task Planning

https://github.com/EdisonNi-hku/when-does-mtl-work

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When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLP

https://github.com/EhsanBitaraf/dataset-mie-literature

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Decoding MIE: A Novel Dataset Approach Using Topic Extraction and Affiliation Parsing

https://github.com/EiraZhang/LACO

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Enhancing Label Correlation Feedback in Multi-Label Text Classification via Multi-Task Learning

https://github.com/ElementAI/beyond-trivial-explanations

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Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations

https://github.com/EleutherAI/The-Pile

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The Pile: An 800GB Dataset of Diverse Text for Language Modeling

https://github.com/EmergenceAI/dartboard

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Better RAG using Relevant Information Gain

https://github.com/Emergent-Behaviors-in-Biology/immune-svm

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Tregs self-organize into a "computing ecosystem" and implement a sophisticated optimization algorithm for mediating immune response

https://github.com/EmmaStensby/poet-morphology

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Co-optimising Robot Morphology and Controller in a Simulated Open-Ended Environment

https://github.com/EndlessSora/DeeperForensics-1.0

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DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection

https://github.com/EndyWon/Deep-Feature-Perturbation

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Diversified Arbitrary Style Transfer via Deep Feature Perturbation

https://github.com/EpistasisLab/digen

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Generative and reproducible benchmarks for comprehensive evaluation of machine learning classifiers

https://github.com/EpistasisLab/penn-ml-benchmarks

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PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison

https://github.com/Eric-Wallace/trickme-interface

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Trick Me If You Can: Human-in-the-loop Generation of Adversarial Examples for Question Answering

https://github.com/Erutan-pku/LCN-for-Chinese-QA

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Lattice CNNs for Matching Based Chinese Question Answering

https://github.com/Faceplugin-ltd/FaceLivenessDetection-Android

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Generalized Face Liveness Detection via De-fake Face Generator

https://github.com/Feng-Hong/DivBS

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Diversified Batch Selection for Training Acceleration

https://github.com/FengleiFan/QAE

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Quadratic Autoencoder (Q-AE) for Low-dose CT Denoising

https://github.com/Fengxiang23/SelectiveMAE

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Scaling Efficient Masked Image Modeling on Large Remote Sensing Dataset

https://github.com/FlappyPeggy/DMAD

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Diversity-Measurable Anomaly Detection

https://github.com/GAIGResearch/Stratega

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Portfolio Search and Optimization for General Strategy Game-Playing

https://github.com/GEM-benchmark/NL-Augmenter

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NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation

https://github.com/GFNOrg/gfn-lm-tuning

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Amortizing intractable inference in large language models

https://github.com/GFNOrg/red-teaming

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Learning diverse attacks on large language models for robust red-teaming and safety tuning

https://github.com/GM-git-dotcom/GM-Score

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GM Score: Incorporating inter-class and intra-class generator diversity, discriminability of disentangled representation, and sample fidelity for evaluating GANs

https://github.com/GauravPandeyLab/lens-learning-ensembles-using-reinforcement-learning

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Developing parsimonious ensembles using predictor diversity within a reinforcement learning framework

https://github.com/GeMoLLM/GeMO

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Generative Monoculture in Large Language Models

https://github.com/GiannisH/Lexicon

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Crowdsourcing for Beyond Polarity Sentiment Analysis A Pure Emotion Lexicon

https://github.com/Godheritage/SCOPE

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SCOPE: Sign Language Contextual Processing with Embedding from LLMs

https://github.com/Group85GP/Group85GP/blob/main/5G_Positioning_Link_Level_Simulator%20v1.0.rar

공식 코드

Link-level simulator for 5G localization

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