← Authors

Shuiwang Ji

58 papers · 2008–2025 · 8 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (17) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (12) 🌈 Renaissance Researcher (9) 🧭 Keyword Pioneer 🀝 Dynamic Duo (13) πŸ‘‘ Triple Crown πŸ† Keyword Champion πŸ† Grand Slam πŸ‘₯ Mega-Team (71) 🌱 Topic Pioneer πŸ”¬ Deep Specialist (11) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter ⚑ Prolific Year (13) πŸ”₯ Unstoppable (8) πŸ—ƒοΈ Keyword Collector (182) πŸ’Ž Century Club (58)

Conferences

ICML (19) NIPS (15) ICLR (14) AAAI (4) ACL (2) JMLR (2) EMNLP (1) IJCAI (1)

Top co-authors

Youzhi Luo (13) Xiner Li (11) Meng Liu (10) Limei Wang (8) Shurui Gui (8) Haiyang Yu (7) Keqiang Yan (7) Yuchao Lin (7) Xiaoning Qian (6) Yi Liu (6)

Keywords

graph neural network (14) self-supervised learning (4) convolutional neural network (4) deep learning (3) encoder-decoder architecture (3) graph structure (3) representation learning (3) periodic invariance (2) large language model (2) hamiltonian matrix (2) model explanation (2) node classification (2) molecular representation (2) 3d graph (2) model interpretability (2) geometric deep learning (2) multimodal learning (2) multiple kernel learning (2) molecular property prediction (2) sparse representation (1)

Papers

EcomScriptBench: A Multi-task Benchmark for E-commerce Script Planning via Step-wise Intention-Driven Product Association ACL 2025
Eliminating Position Bias of Language Models: A Mechanistic Approach ICLR 2025
Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models ICLR 2025
Learning to Discover Regulatory Elements for Gene Expression Prediction ICLR 2025
Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design ICML 2025
Discovering Physics Laws of Dynamical Systems via Invariant Function Learning ICML 2025
On Explaining Equivariant Graph Networks via Improved Relevance Propagation ICML 2025
DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra ICML 2025
Geometry Informed Tokenization of Molecules for Language Model Generation ICML 2025
Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs Reasoning ACL 2025
Complete and Efficient Graph Transformers for Crystal Material Property Prediction ICLR 2024
Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation NIPS 2024
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction ICML 2024
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency ICML 2024
Graph Structure Extrapolation for Out-of-Distribution Generalization ICML 2024
Position: TrustLLM: Trustworthiness in Large Language Models ICML 2024
A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery EMNLP 2024
SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations ICLR 2024
On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods ICLR 2024
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm ICLR 2024
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization NIPS 2023
Graph Mixup with Soft Alignments ICML 2023
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian ICML 2023
Group Equivariant Fourier Neural Operators for Partial Differential Equations ICML 2023
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules NIPS 2023
Towards Symmetry-Aware Generation of Periodic Materials NIPS 2023
A new perspective on building efficient and expressive 3D equivariant graph neural networks NIPS 2023
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction ICML 2023
Learning Hierarchical Protein Representations via Complete 3D Graph Networks ICLR 2023
Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models ICLR 2023
Automated Data Augmentations for Graph Classification ICLR 2023
Learning Fair Graph Representations via Automated Data Augmentations ICLR 2023
Video Timeline Modeling For News Story Understanding NIPS 2023
Task-Agnostic Graph Explanations NIPS 2022
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs NIPS 2022
GOOD: A Graph Out-of-Distribution Benchmark NIPS 2022
Periodic Graph Transformers for Crystal Material Property Prediction NIPS 2022
An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch ICLR 2022
Spherical Message Passing for 3D Molecular Graphs ICLR 2022
Generating 3D Molecules for Target Protein Binding ICML 2022
Self-Supervised Representation Learning via Latent Graph Prediction ICML 2022
GraphFM: Improving Large-Scale GNN Training via Feature Momentum ICML 2022
On Explainability of Graph Neural Networks via Subgraph Explorations ICML 2021
GraphDF: A Discrete Flow Model for Molecular Graph Generation ICML 2021
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs NIPS 2021
Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence NIPS 2021
DIG: A Turnkey Library for Diving into Graph Deep Learning Research JMLR 2021
Adaptive Convolutional ReLUs AAAI 2020
A Multi-Scale Approach for Graph Link Prediction AAAI 2020
Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising NIPS 2020
StructPool: Structured Graph Pooling via Conditional Random Fields ICLR 2020
Non-Local U-Nets for Biomedical Image Segmentation AAAI 2020
Graph U-Nets ICML 2019
Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods AAAI 2019
Dense Transformer Networks for Brain Electron Microscopy Image Segmentation IJCAI 2019
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions NIPS 2018
Multi-class Discriminant Kernel Learning via Convex Programming JMLR 2008
Multi-label Multiple Kernel Learning NIPS 2008