Wanyu Lin

16 papers · 2020–2026 · 6 conferences · across top CS/AI conferences

Achievements

+9 more ↓

🌍 Conference Polyglot (6) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏃 Academic Marathon (5)

🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) 🏆 Grand Slam 🗃️ Keyword Collector (60) ⚡ Prolific Year (5) 💎 Century Club (13) 🔥 Unstoppable (6) ❓ The Questioner

Conferences

AAAI (6) ICML (5) CVPR (2) ICCV (1) ICLR (1) NIPS (1)

Top co-authors

Qinghua Hu (3) Kay Chen Tan (3) Baochun Li (3) Pengfei Zhu (3) Yu Wang (3) Haokai Hong (2) Min Jiang (2) Zhenzhong Wang (2) Pan Zhou (2) Weihao Li (2)

Research topics

Privacy (1)

Keywords

graph neural network (7) node classification (2) causal inference (2) metric learning (1) algorithmic fairness (1) neural network security (1) few-shot learning (1) image restoration (1) feature extraction (1) backdoor defense (1) knowledge distillation (1) depth estimation (1) image dehazing (1) explainable ai (1) graph representation (1) geometric deep learning (1) computational efficiency (1) granger causality (1) model interpretability (1) transfer learning (1)

Papers

Revisiting the Canonicalization for Fast and Accurate Crystal Tensor Property Prediction AAAI 2026 S-DAG: A Subject-Based Directed Acyclic Graph for Multi-Agent Heterogeneous Reasoning AAAI 2026 Distributional Priors Guided Diffusion for Generating 3D Molecules in Low Data Regimes AAAI 2026 Backdoor Defense via Enhanced Splitting and Trap Isolation ICCV 2025 HPS: Hard Preference Sampling for Human Preference Alignment ICML 2025 Accelerating 3D Molecule Generation via Jointly Geometric Optimal Transport ICLR 2025 Latent Imputation before Prediction: A New Computational Paradigm for De Novo Peptide Sequencing ICML 2025 Socialized Coevolution: Advancing a Better World through Cross-Task Collaboration ICML 2025 What Matters in Graph Class Incremental Learning? An Information Preservation Perspective NIPS 2024 SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency AAAI 2024 Generating Diagnostic and Actionable Explanations for Fair Graph Neural Networks AAAI 2024 Socialized Learning: Making Each Other Better Through Multi-Agent Collaboration ICML 2024 Robust Graph Meta-Learning via Manifold Calibration with Proxy Subgraphs AAAI 2023 OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks CVPR 2022 Generative Causal Explanations for Graph Neural Networks ICML 2021 Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data CVPR 2020