https://github.com/lucylow/En_francais_si_vous_plait-
Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models
Papers with Code 아카이브
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/luke-grassroot/scratchgan
https://github.com/lukedeo/keras-acgan
https://github.com/lukemelas/unsupervised-image-segmentation
https://github.com/luomancs/retriever_reader_for_okvqa
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/lusinlu/skipnet_evaluation
https://github.com/lvyufeng/MindSpore-GAN
https://github.com/lyh6560new/p3sum
https://github.com/lyken17/pytorch
https://github.com/lyn1874/fedssyn
On the effectiveness of partial variance reduction in federated learning with heterogeneous data
https://github.com/lynfi/ADP
Improving Adversarial Robustness via Promoting Ensemble Diversity
https://github.com/lyqcom/2D-unet
https://github.com/machenslab/dPCA
https://github.com/machine-intelligence-laboratory/OptimalNumberOfTopics
https://github.com/maheshmylavarapu0057/QueryBasedSummarisation
Diversity driven Attention Model for Query-based Abstractive Summarization
https://github.com/makarandtapaswi/MovieQA_benchmark
MovieQA: Understanding Stories in Movies through Question-Answering
https://github.com/makcedward/nlpaug
https://github.com/mangoubi/Min-max-optimization-algorithm-for-training-GANs
https://github.com/manicman1999/Sword-GAN32
https://github.com/manikandan-ravikiran/complex-assignments
https://github.com/mankmonjre/k-DPP-reco-engine
Low-Rank Factorization of Determinantal Point Processes for Recommendation
https://github.com/manu-sk/rnn_chatbot
A Diversity-Promoting Objective Function for Neural Conversation Models
https://github.com/map-learning/tl2la
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
https://github.com/marccanby/bidi_decoding
Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models
https://github.com/marcojira/fls
https://github.com/marcomanciniunitn/Master-Thesis-Project
Building a Conversational Agent Overnight with Dialogue Self-Play
https://github.com/marinadominguez/diffusion-for-us-images
https://github.com/marload/ConvNets-TensorFlow2
PolyNet: A Pursuit of Structural Diversity in Very Deep Networks
https://github.com/martin-danelljan/ECO
https://github.com/marumse/colorize_images
https://github.com/masakhane-io/masakhane
Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages
https://github.com/mathllm/math-v
Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset
https://github.com/mattgorb/cnn_bold5000
https://github.com/mattiasu96/TrapGenerator
https://github.com/mattiasxu/VQVAE-2
https://github.com/mattiasxu/Video-VQVAE
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.