Papers with Code 아카이브

Benchmarking

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

https://github.com/ilialarchenko/abstract_reasoning

On the Measure of Intelligence

https://github.com/ilias-vrg/ilias

ILIAS: Instance-Level Image retrieval At Scale

https://github.com/iml-dkfz/sf-visuals

A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification

https://github.com/implus/CarDetectionExample

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/intelligent-computing-lab-yale/spikesim

SpikeSim: An end-to-end Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks

https://github.com/inyong37/Vision

Benchmarking Single Image Dehazing and Beyond

https://github.com/ironbar/AnimalAI-Olympics

EvalAI: Towards Better Evaluation Systems for AI Agents

https://github.com/ivMCL/AttentiveNorm_Detection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/ivan-chai/torch-linear-assignment

HoTPP Benchmark: Are We Good at the Long Horizon Events Forecasting?

https://github.com/iyerkrithika21/mesh2ssm_2023

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

https://github.com/jachiam/cpo

Benchmarking Deep Reinforcement Learning for Continuous Control

https://github.com/jacksonchen1998/Cold-Start-Reinforcement-Learning-with-Softmax-Policy-Gradient

CIDEr: Consensus-based Image Description Evaluation

https://github.com/jacobdeasy/flexible-ehr

Multitask learning and benchmarking with clinical time series data

https://github.com/jacobtyo/mudd

Torchreid: A Library for Deep Learning Person Re-Identification in Pytorch

https://github.com/jajajajaja121/mmdetection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/jannik-brinkmann/multilingual-features

CausalGym: Benchmarking causal interpretability methods on linguistic tasks

https://github.com/jasonakoun/signsgd-fault-tolerance

signSGD with Majority Vote is Communication Efficient And Fault Tolerant

https://github.com/jbellis/jvector

Accelerating Large-Scale Inference with Anisotropic Vector Quantization

https://github.com/jerrytony/mmdetection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/jertubiana/ProteinMotifRBM

Learning protein constitutive motifs from sequence data

https://github.com/jeykigung/P5

OpenP5: An Open-Source Platform for Developing, Training, and Evaluating LLM-based Recommender Systems

https://github.com/jhaprince/multibully

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/jichengYUAN/mmdetectionCust

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/jielin-qiu/mm_robustness

Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift

https://github.com/jim-schwoebel/allie

GAMA: a General Automated Machine learning Assistant

https://github.com/jincan333/lot

CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms

https://github.com/jinfagang/manadet

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/jinhaoduan/sar

Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph

https://github.com/jinhaoduan/shifting-attention-to-relevance

Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph

https://github.com/jireh-father/mmdetection_210507

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/jixiaozhong/RealSR

NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results

https://github.com/jk96491/C-COMA

The StarCraft Multi-Agent Challenge

https://github.com/jk96491/SMAC

The StarCraft Multi-Agent Challenge

https://github.com/jkcrosby3/FashionMNST

Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

https://github.com/jkooy/Parameter-efficient-Fine-tuning-for-Vision-Transformers

Parameter-efficient Model Adaptation for Vision Transformers

https://github.com/jmhessel/pycocoevalcap

CIDEr: Consensus-based Image Description Evaluation

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