https://github.com/edward-sun/difusco
공식 코드DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization
Papers with Code 아카이브
Combinatorial Optimization
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Combinatorial Optimization is a category of problems which requires optimizing a function over a combination of discrete objects and the solutions are constrained. Examples include finding shortest paths in a graph, maximizing value in the Knapsack problem and finding boolean settings that satisfy a set of constraints. Many of these problems are NP-Hard, which means that no polynomial time solution can be developed for them. Instead, we can only produce approximations in polynomial time that are guaranteed to be some factor worse than the true optimal solution.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/etrommer/agn-approx
공식 코드Combining Gradients and Probabilities for Heterogeneous Approximation of Neural Networks
https://github.com/facebookresearch/neural-rewriter
공식 코드Learning to Perform Local Rewriting for Combinatorial Optimization
https://github.com/farid-najar/transportersdilemma
공식 코드https://github.com/feiliu36/eoh
공식 코드Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model
https://github.com/feiliu36/mtnco
공식 코드Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization
https://github.com/feiliu36/promptvrp
공식 코드https://github.com/flyingdoog/PGExplainer
공식 코드DAG Matters! GFlowNets Enhanced Explainer For Graph Neural Networks
https://github.com/francescofoglino/Curriculum-Learning
공식 코드https://github.com/futianfan/reinforced-genetic-algorithm
공식 코드Reinforced Genetic Algorithm for Structure-based Drug Design
https://github.com/fuxiailab/rl4rs
공식 코드RL4RS: A Real-World Dataset for Reinforcement Learning based Recommender System
https://github.com/gaocrr/elg
공식 코드https://github.com/gaoly/mopn
공식 코드Multi-objective Pointer Network for Combinatorial Optimization
https://github.com/geminilight/hrl-acra
공식 코드https://github.com/giancarlo-catalano/ps_minimal_showcase
공식 코드Mining Potentially Explanatory Patterns via Partial Solutions
https://github.com/gitgelila/tempseq
공식 코드https://github.com/google-research/google-research
공식 코드ES-ENAS: Efficient Evolutionary Optimization for Large Hybrid Search Spaces
https://github.com/google-research/google-research/tree/master/correlation_clustering
공식 코드https://github.com/google-research/tf-opt
공식 코드Reinforcement Learning with Combinatorial Actions: An Application to Vehicle Routing
https://github.com/google-research/unique-randomizer
공식 코드Incremental Sampling Without Replacement for Sequence Models
https://github.com/graph-com/co_proxydesign
공식 코드Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation
https://github.com/graph-com/meta_co
공식 코드Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning
https://github.com/grimmlab/gumbeldore
공식 코드Self-Improvement for Neural Combinatorial Optimization: Sample without Replacement, but Improvement
https://github.com/grimmlab/policy-based-self-competition
공식 코드https://github.com/grimmlab/step-and-reconsider
공식 코드Take a Step and Reconsider: Sequence Decoding for Self-Improved Neural Combinatorial Optimization
https://github.com/guanyucui/mgnn
공식 코드MGNN: Graph Neural Networks Inspired by Distance Geometry Problem
https://github.com/guetye/dhrl-fnmr
공식 코드https://github.com/hazimehh/L0Learn
공식 코드Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms
https://github.com/hci-unihd/branchedot
공식 코드Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources
https://github.com/henry-yeh/DeepACO
공식 코드DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization
https://github.com/huawei-noah/trustworthyAI
공식 코드https://github.com/hunni10/DelaunayDataset
공식 코드Learning Geometric Combinatorial Optimization Problems using Self-attention and Domain Knowledge
https://github.com/idea-iitd/GCOMB
공식 코드Learning Heuristics over Large Graphs via Deep Reinforcement Learning
https://github.com/ijh85/quantum-dynamic-programming
공식 코드Dynamic Programming on a Quantum Annealer: Solving the RBC Model
https://github.com/ilanashapiro/constraints_project
공식 코드Synthesizing Composite Hierarchical Structure from Symbolic Music Corpora
https://github.com/informsjoc/2023.0281
공식 코드Multi-Objective Linear Ensembles for Robust and Sparse Training of Few-Bit Neural Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.