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

https://github.com/jmorrison57/ContinualLearningProject

CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions

https://github.com/jms0923/mmdet_tta

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/johnsonkee/graduate_design

Technical Report on the CleverHans v2.1.0 Adversarial Examples Library

https://github.com/johntiger1/multimodal_fairness

Multitask learning and benchmarking with clinical time series data

https://github.com/jorisvandenbossche/target-encoder-benchmarks

OpenML Benchmarking Suites

https://github.com/josepatino/Voice-Privacy-Challenge-2020

Introducing the VoicePrivacy Initiative

https://github.com/js-aguiar/wheat-object-detection

Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods

https://github.com/jsong0327/HumanDetectionServer

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/judge0/judge0

ECCO: Can We Improve Model-Generated Code Efficiency Without Sacrificing Functional Correctness?

https://github.com/jugg1er/air

The StarCraft Multi-Agent Challenge

https://github.com/jwwangchn/mmdet-aitod

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/jxbz/signSGD

signSGD with Majority Vote is Communication Efficient And Fault Tolerant

https://github.com/jzlei/scEntropy

Single-cell entropy to quantify the cellular transcription from single-cell RNA-seq data

https://github.com/kaiko-ai/eva

Benchmarking Self-Supervised Learning on Diverse Pathology Datasets

https://github.com/kakaobrain/honeybee

MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

https://github.com/kaushikb258/Habitat_RL

Habitat: A Platform for Embodied AI Research

https://github.com/kcorder/qmix_variants

The StarCraft Multi-Agent Challenge

https://github.com/kenjyoung/MinAtar

The Arcade Learning Environment: An Evaluation Platform for General Agents

https://github.com/kinalmehta/epymarl

The StarCraft Multi-Agent Challenge

https://github.com/kinit-sk/imgtb

MGTBench: Benchmarking Machine-Generated Text Detection

https://github.com/kirangpcet/KRCCTumor

The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes

https://github.com/kirubarajan/roft

Automatic Detection of Generated Text is Easiest when Humans are Fooled

https://github.com/kirubarajan/trick

Automatic Detection of Generated Text is Easiest when Humans are Fooled

https://github.com/kl-lab/fuma

GRATIS: GeneRAting TIme Series with diverse and controllable characteristics

https://github.com/kl-lab/gratis

GRATIS: GeneRAting TIme Series with diverse and controllable characteristics

https://github.com/klemens-floege/oneprot

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/konyul/mmdet3d

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/korotulea/Quantifying-Hippocampus-Volume-for-Alzheimers-Progression-AI-Assistant

A large annotated medical image dataset for the development and evaluation of segmentation algorithms

https://github.com/ktw361/mmdetection_impl

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/kynkaat/role-of-imagenet-classes-in-fid

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/lackel/hierarchical_weighted_scl

Benchmarking Natural Language Understanding Services for building Conversational Agents

https://github.com/lackel/sdc

Benchmarking Natural Language Understanding Services for building Conversational Agents

https://github.com/lamalab-org/mac-bench

Are large language models superhuman chemists?

https://github.com/laurendelong21/mars

Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphs

https://github.com/lavoiems/Cats-UDT

Moment Matching for Multi-Source Domain Adaptation

https://github.com/lavoiems/SADt

Moment Matching for Multi-Source Domain Adaptation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.