MIRA Lab's Projects
This is the code for our paper "Reinforcement Learning within Tree Search for Fast Macro Placement".
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.
ChiPBench:Benchmarking End-to-End Performance of AI-based Chip Placement Algorithms
Results and data for reinforcement learning algorithms.
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
A novel template-free retrosynthesizer that can generate diverse sets of reactants for a desired product via discrete conditional variational autoencoders.
Must-read papers on Entity Alignment
The code of paper Rethinking Graph Convolutional Networks in Knowledge Graph Completion. Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu. WWW 2022.
The code of paper LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence. Zhihao Shi, Xize Liang, Jie Wang. ICLR 2023.
The code of paper Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation. Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu. SIGKDD 2022.
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.
The code of paper Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion. Zhanqiu Zhang, Jianyu Cai, Jie Wang. NeurIPS 2020.
The code of paper Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang. AAAI 2020.
Must-read papers on Knowledge Graph Embedding
Must-read papers on Knowledge Graph Reasoning (KGR)
This is the code for G2MILP, a deep learning-based mixed-integer linear programming (MILP) instance generator.
The code of paper *Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph*.
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.
The code of paper *Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework*.
MIRA Book for Reinforcement Learning (draft)
MIRA Book for Representation Learning (draft)
The PySCIPOpt codes used for machine learning purposes. Forked from https://github.com/ds4dm/PySCIPOpt.git .
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.
The code of paper *Promoting Stochasticity for Expressive Policies viaa Simple and Efficient Regularization Method*.