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fdd-defense
PublicDefense of adversarial attacks on FDD models. fdd-defense is a python library with adversarial attacks on Fault Detection and Diagnostic (FDD) models and defense methods against attacks.- nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset
- This repository contains a deep learning-based approach for improving A* search efficiency on grid graphs. By learning instance-dependent heuristic proxies like correction factors and path probability, our method significantly reduces computational effort in obstacle-rich environments.
- Benchmarking fault detection and diagnosis methods
al_toolbox
PublicOmniFusion
PublicStyleFeatureEditor
PublicGuide-and-Rescale
Publicskill-fusion
PublicWaRP
Publicsmm
Publichim-agent
Publiclearn-to-follow
Publicwhen-to-switch
Publicmats-lp
PublicRATE
PublicIGOR
Publicpogema-benchmark
Publicpogema-toolbox
Publicpogema
PublicMAPF-GPT
PublicThis repository contains MAPF-GPT, a deep learning-based model for solving MAPF problems. Trained with imitation learning on trajectories produced by LaCAM, it generates collision-free paths under partial observability without heuristics or agent communication. MAPF-GPT excels on unseen instances and outperforms state-of-the-art solvers.gnn-tam
PublicScalable-SASRec
Publicaij_marl_baseline
PublicPublic Baseline for AIJ Multi-Agent RL Contest