MIRA Lab
Laboratory of Machine Intelligence Research and Applications at University of Science and Technology of China
University of Science and Technology of China, Hefei
Pinned Repositories
AI4Sci-MiCaM
This is the code of paper "De Novo Molecular Generation via Connection-aware Motif Mining". Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu. ICLR 2023.
GCN4KGC
The code of paper Rethinking Graph Convolutional Networks in Knowledge Graph Completion. Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu. WWW 2022.
GNN-LMC
The code of paper LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence. Zhihao Shi, Xize Liang, Jie Wang. ICLR 2023.
GraphAKD
The code of paper Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation. Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu. SIGKDD 2022.
KG-TACT
The code of paper Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs. Jiajun Chen, Huarui He, Feng Wu, Jie Wang. AAAI 2021.
KGE-DURA
The code of paper Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion. Zhanqiu Zhang, Jianyu Cai, Jie Wang. NeurIPS 2020.
KGE-HAKE
The code of paper Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang. AAAI 2020.
L2O-HEM-Torch
The code of paper Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model. Zhihai Wang, Xijun Li, Jie Wang*, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu. ICLR 2023.
QE-ConE
The code of paper ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs. Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu. NeurIPS 2021.
RLPapers
Must-read papers on Reinforcement Learning (RL)
MIRA Lab's Repositories
MIRALab-USTC/KGE-HAKE
The code of paper Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang. AAAI 2020.
MIRALab-USTC/GCN4KGC
The code of paper Rethinking Graph Convolutional Networks in Knowledge Graph Completion. Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu. WWW 2022.
MIRALab-USTC/L2O-HEM-Torch
The code of paper Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model. Zhihai Wang, Xijun Li, Jie Wang*, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu. ICLR 2023.
MIRALab-USTC/AI4Sci-MiCaM
This is the code of paper "De Novo Molecular Generation via Connection-aware Motif Mining". Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu. ICLR 2023.
MIRALab-USTC/KGE-DURA
The code of paper Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion. Zhanqiu Zhang, Jianyu Cai, Jie Wang. NeurIPS 2020.
MIRALab-USTC/QE-ConE
The code of paper ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs. Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu. NeurIPS 2021.
MIRALab-USTC/GNN-LMC
The code of paper LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence. Zhihao Shi, Xize Liang, Jie Wang. ICLR 2023.
MIRALab-USTC/KG-TACT
The code of paper Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs. Jiajun Chen, Huarui He, Feng Wu, Jie Wang. AAAI 2021.
MIRALab-USTC/GraphAKD
The code of paper Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation. Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu. SIGKDD 2022.
MIRALab-USTC/L2O-G2MILP
This is the code for G2MILP, a deep learning-based mixed-integer linear programming (MILP) instance generator.
MIRALab-USTC/ChiPBench
ChiPBench:Benchmarking End-to-End Performance of AI-based Chip Placement Algorithms
MIRALab-USTC/RL-CMBAC
The code of paper Sample-Efficient Reinforcement Learning via Conservative Model-Based Actor-Critic. Zhihai Wang, Jie Wang*, Qi Zhou, Bin Li, Houqiang Li. AAAI 2022.
MIRALab-USTC/RL-SCPO
The code of paper *Learning Robust Policy against Disturbance in Transition Dynamics via State-Conservative Policy Optimization*.
MIRALab-USTC/RL-SPF
a representation learning method that predicts the Fourier transform of state sequences to improve sample efficiency of RL algorithms.
MIRALab-USTC/AI4EDA-EfficientPlace
This is the code for our paper "Reinforcement Learning within Tree Search for Fast Macro Placement".
MIRALab-USTC/DD-RetroDCVAE
A novel template-free retrosynthesizer that can generate diverse sets of reactants for a desired product via discrete conditional variational autoencoders.
MIRALab-USTC/AI4LogicSynthesis-PruneX
MIRALab-USTC/KDDCup2021_WikiKG90M_GraphMIRAcles
MIRALab-USTC/LD
MIRALab-USTC/RL-CBM
The code of paper Robust Representation learning by Clustering with Bisimulation Metrics for Visual Reinforcement Learning with Distractions. Qiyuan Liu, Qi Zhou, Rui Yang, Jie Wang. AAAI 2023.
MIRALab-USTC/RL-CRESP
MIRALab-USTC/RL-TRACER
MIRALab-USTC/RL-RAEB
This is the code for the paper "Efficient Exploration in Resource-Restricted Reinforcement Learning" (https://arxiv.org/abs/2212.06988)
MIRALab-USTC/DCRN
This is the code of paper Deep Cognitive Reasoning Network for Multi-hop Question Answering over Knowledge Graphs. Jianyu Cai, Zhanqiu Zhang, Feng Wu, Jie Wang. Findings of ACL 2021
MIRALab-USTC/L2O-Symb4CO
The code of paper *Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework*.
MIRALab-USTC/AI4EDA_TNet
MIRALab-USTC/scip
The scip codes used for machine learning purposes. Downloaded from https://www.scipopt.org/index.php#download
MIRALab-USTC/L2O-GS4CO
The code of paper *Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph*.
MIRALab-USTC/PySCIPOpt
The PySCIPOpt codes used for machine learning purposes. Forked from https://github.com/ds4dm/PySCIPOpt.git .
MIRALab-USTC/UKB-MITH