https://github.com/DeepPSP/torch_ecg/blob/master/torch_ecg/models/unets/ecg_unet.py
LUDB: a new open-access validation tool for electrocardiogram delineation algorithms
Papers with Code 아카이브
Diversity
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 0
- 보존된 평가 기록
- 0
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/DeepakSridhar/fgdm
https://github.com/Demonhesusheng/Reid
https://github.com/DerrickXuNu/OpenCOOD
Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds
https://github.com/Digby-L/GNN-Conversation-Graph
https://github.com/DinaSolitah/Skin-Disease-Analyzer
https://github.com/E-kitcher/MSc-Project-
https://github.com/ETS-Research-Repositories/deep-clustering-toolbox
https://github.com/EcoJulia/Diversity.jl
https://github.com/EgorRazumilov/TAC_GAN
TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network
https://github.com/EleutherAI/GPTNeo
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
https://github.com/EleutherAI/gpt-neo
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
https://github.com/EliasKassapis/CARMSS
A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities
https://github.com/EliasKassapis/CARSSS
A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities
https://github.com/EugenHotaj/pytorch-generative/blob/master/pytorch_generative/models/vae/vq_vae_2.py
https://github.com/FaceOnLive/Face-Liveness-Detection-SDK-Android
https://github.com/FaceOnLive/Face-Recognition-SDK-Android
Controllable and Guided Face Synthesis for Unconstrained Face Recognition
https://github.com/Faceplugin-ltd/FaceRecognition-Android
Controllable and Guided Face Synthesis for Unconstrained Face Recognition
https://github.com/FenHua/transfer_adv
Improving Adversarial Transferability with Gradient Refining
https://github.com/FreedomIntelligence/PlatoLM
PlatoLM: Teaching LLMs in Multi-Round Dialogue via a User Simulator
https://github.com/GenesisDCarmen/C_Reconocimiento_Facial
https://github.com/GraphGrailAi/DialoGPT
A Diversity-Promoting Objective Function for Neural Conversation Models
https://github.com/Guang000/Awesome-Dataset-Distillation
DREAM: Efficient Dataset Distillation by Representative Matching
https://github.com/Guy-Shapira/DeepInversion
Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion
https://github.com/Heumi/BEGAN-tensorflow
https://github.com/HoganZhang/pytorch-vsumm-reinforce
https://github.com/HsinYingLee/MDMM
Diverse Image-to-Image Translation via Disentangled Representations
https://github.com/Hydrino/ACGAN_cifar10
https://github.com/Hydrino/ACGAN_mnist
https://github.com/IBM/IRM-games
Treatment Effect Estimation using Invariant Risk Minimization
https://github.com/IBerdinskikh/NCSR
Noise Conditional Flow Model for Learning the Super-Resolution Space
https://github.com/IVRL/w2s
Fully Unsupervised Diversity Denoising with Convolutional Variational Autoencoders
https://github.com/JPlin/MSGAN
Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis
https://github.com/JShubhM15/recommender_systems
Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems
https://github.com/Janspiry/Palette-Image-to-Image-Diffusion-Models
https://github.com/JdeRobot/BehaviorSuite
Scalability in Perception for Autonomous Driving: Waymo Open Dataset
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.