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Scheduling

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

https://github.com/zhongyuanzhao/gcn-dql

공식 코드

Delay-Oriented Distributed Scheduling Using Graph Neural Networks

https://github.com/zhongyuanzhao/gcn-sparsify

공식 코드

Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks

https://github.com/zhongyuanzhao/multihop-offload

공식 코드

Congestion-aware Distributed Task Offloading in Wireless Multi-hop Networks Using Graph Neural Networks

https://github.com/zhouzypaul/auto_eval

공식 코드

AutoEval: Autonomous Evaluation of Generalist Robot Manipulation Policies in the Real World

https://github.com/zzzace2000/autodiagnosis

공식 코드

Dynamic Measurement Scheduling for Event Forecasting using Deep RL

https://gitlab.com/hdonancio/pumpscheduling

공식 코드

The Pump Scheduling Problem: A Real-World Scenario for Reinforcement Learning

https://gitlab.com/jmoederl/fast-variational-block-sparse-bayesian-learning

공식 코드

Fast Variational Block-Sparse Bayesian Learning

https://gitlab.com/ryuan/ieee-cis-data-challenge-fresno

공식 코드

Optimal activity and battery scheduling algorithm using load and solar generation forecast

https://gitlab.com/xrl2/chat4xai

공식 코드

An AI Chatbot for Explaining Deep Reinforcement Learning Decisions of Service-oriented Systems

https://github.com/2023-MindSpore-4/Code13/tree/main/zhanglan/MLink-main

MLink: Linking Black-Box Models from Multiple Domains for Collaborative Inference

https://github.com/2023-MindSpore-4/Code13/tree/main/zhanglan/MLink-main/mlink_ms

MLink: Linking Black-Box Models from Multiple Domains for Collaborative Inference

https://github.com/AlanFokCo/compensation-tools

Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources

https://github.com/ArchieGertsman/spark-sched-sim

Learning Scheduling Algorithms for Data Processing Clusters

https://github.com/AsmaBALAMANE/tiramisu

Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code

https://github.com/BFTrainer/BFTrainer

BFTrainer: Low-Cost Training of Neural Networks on Unfillable Supercomputer Nodes

https://github.com/BFTrainer/Replayer

BFTrainer: Low-Cost Training of Neural Networks on Unfillable Supercomputer Nodes

https://github.com/CAMMA-public/ai4surgery

EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos

https://github.com/CAMMA-public/cholect50

EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos

https://github.com/DrKenReid/FactorioBeltProblemGECCO

The Factory Must Grow: Automation in Factorio

https://github.com/EpiSci/SoCRATES

DeepSoCS: A Neural Scheduler for Heterogeneous System-on-Chip (SoC) Resource Scheduling

https://github.com/GeminiLight/virne

FlagVNE: A Flexible and Generalizable Reinforcement Learning Framework for Network Resource Allocation

https://github.com/Huawei-MRC-OSI/optml-zoo

Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code

https://github.com/IntelligentRoboticsLabs/ros2_planning_system

PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains

https://github.com/MK-tech20/MDRRT-scheduling-dwave

Solving Large Break Minimization Problems in a Mirrored Double Round-robin Tournament Using Quantum Annealing

https://github.com/MachineLearningSystem/25MLSYS-NEO

NEO: Saving GPU Memory Crisis with CPU Offloading for Online LLM Inference

https://github.com/MattJud/gnn_jssp

Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning

https://github.com/MindSpore-scientific-2/code-5/tree/main/cyclic-cosine-decay-master

Stochastic Gradient Descent with Hyperbolic-Tangent Decay on Classification

https://github.com/MindSpore-scientific/code-4/tree/main/cyclic-cosine-decay-master

Stochastic Gradient Descent with Hyperbolic-Tangent Decay on Classification

https://github.com/Mishuni/ViT_Inversion

GradViT: Gradient Inversion of Vision Transformers

https://github.com/OpenLLMAI/OpenLLaMA2

OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework

https://github.com/OrangeSodahub/RMMDet

RMMDet: Road-Side Multitype and Multigroup Sensor Detection System for Autonomous Driving

https://github.com/RichardBean/IEEE-Predict-Optimize-Challenge

Using solar and load predictions in battery scheduling at the residential level

https://github.com/Sheepsody/Batched-Impala-PyTorch

Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU

https://github.com/TUDB-Labs/mLoRA

mLoRA: Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs

https://github.com/Tiramisu-Compiler/tiramisu

Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code

https://github.com/YuemingJin/MTRCNet-CL

EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos

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