← Authors

Peilin Zhao

91 papers · 2009–2026 · 13 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (15) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (16) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (13) πŸ—ΊοΈ Taxonomy Completionist (31) 🏠 Conference Loyalist (20) 🀝 Dynamic Duo (18) πŸ‘‘ Triple Crown πŸ† Keyword Champion πŸ† Grand Slam πŸ”¬ Deep Specialist (12) 🧬 Topic Evolution πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (13) πŸ’Ž Century Club (90) πŸ—ƒοΈ Keyword Collector (92) ⚑ Prolific Year (7)

Conferences

ICML (20) IJCAI (16) AAAI (14) ICLR (12) NIPS (12) AISTATS (3) CVPR (3) JMLR (3) ACML (2) EMNLP (2) ICCV (2) ACL (1) WACV (1)

Top co-authors

Junzhou Huang (18) Yatao Bian (12) Liu Liu (8) Mingkui Tan (8) Lanqing Li (7) Jiaxiang Wu (7) Yu Rong (7) Bingzhe Wu (7) Tingyang Xu (7) Pengcheng Wu (6)

Research topics

Reinforcement Learning (1)

Keywords

graph neural network (11) online learning (10) stochastic optimization (4) generative model (3) decentralized optimization (3) distributed learning (3) molecular representation (3) time series forecasting (3) regret bound (3) representation learning (3) multi-task learning (3) domain generalization (3) reaction prediction (3) in-context learning (2) test-time adaptation (2) reinforcement learning (2) deep reinforcement learning (2) similarity learning (2) video understanding (2) active learning (2)

Papers

CrystalDiT: Simple Diffusion Transformers for Crystal Generation AAAI 2026
HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting AAAI 2025
Injecting Imbalance Sensitivity for Multi-Task Learning IJCAI 2025
Measuring Diversity in Synthetic Datasets ICML 2025
Test-time Adapted Reinforcement Learning with Action Entropy Regularization ICML 2025
NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction ICML 2025
Self-Bootstrapping for Versatile Test-Time Adaptation ICML 2025
Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples ICML 2025
Efficient Parallel Training Methods for Spiking Neural Networks with Constant Time Complexity ICML 2025
IgGM: A Generative Model for Functional Antibody and Nanobody Design ICLR 2025
COME: Test-time Adaption by Conservatively Minimizing Entropy ICLR 2025
TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting ICLR 2025
Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models ICLR 2025
Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model AAAI 2025
Scaling Diffusion Language Models via Adaptation from Autoregressive Models ICLR 2025
Latent Diffusion Transformer for Probabilistic Time Series Forecasting AAAI 2024
SDformer: Similarity-driven Discrete Transformer For Time Series Generation NIPS 2024
WatME: Towards Lossless Watermarking Through Lexical Redundancy ACL 2024
LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay EMNLP 2024
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations ICLR 2024
SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases ICLR 2024
Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution ICLR 2024
Test-Time Model Adaptation with Only Forward Passes ICML 2024
Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization ICML 2024
Towards Geometric Normalization Techniques in SE(3) Equivariant Graph Neural Networks for Physical Dynamics Simulations IJCAI 2024
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization ICLR 2023
BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion ICLR 2023
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery – a Focus on Affinity Prediction Problems with Noise Annotations AAAI 2023
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder AAAI 2023
Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction IJCAI 2023
A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges IJCAI 2023
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification AAAI 2023
Class-Conditional Sharpness-Aware Minimization for Deep Long-Tailed Recognition CVPR 2023
On the Pitfall of Mixup for Uncertainty Calibration CVPR 2023
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection NIPS 2023
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning ICML 2023
Fairness-guided Few-shot Prompting for Large Language Models NIPS 2023
Retaining Beneficial Information from Detrimental Data for Neural Network Repair NIPS 2023
Towards Stable Test-time Adaptation in Dynamic Wild World ICLR 2023
Learning Neural Set Functions Under the Optimal Subset Oracle NIPS 2022
SVIP: Sequence VerIfication for Procedures in Videos CVPR 2022
$p$-Laplacian Based Graph Neural Networks ICML 2022
Local Augmentation for Graph Neural Networks ICML 2022
Efficient Test-Time Model Adaptation without Forgetting ICML 2022
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup NIPS 2022
GNN-Retro: Retrosynthetic Planning with Graph Neural Networks AAAI 2022
AdaXpert: Adapting Neural Architecture for Growing Data ICML 2021
Hierarchical Graph Capsule Network AAAI 2021
Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation ICCV 2021
Meta-learning with an Adaptive Task Scheduler NIPS 2021
Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization AISTATS 2021
PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning AAAI 2021
Context-Aware Domain Adaptation in Semantic Segmentation WACV 2021
Meta-learning Hyperparameter Performance Prediction with Neural Processes ICML 2021
Contextualized Point-of-Interest Recommendation IJCAI 2020
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search ICML 2020
Adversarial Sparse Transformer for Time Series Forecasting NIPS 2020
RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist NIPS 2020
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks AAAI 2020
Relation-Aware Transformer for Portfolio Policy Learning IJCAI 2020
Aggregated Gradient Langevin Dynamics AAAI 2020
Towards Fast Adaptation of Neural Architectures with Meta Learning ICLR 2020
Mastering Complex Control in MOBA Games with Deep Reinforcement Learning AAAI 2020
Complexities in Projection-Free Stochastic Non-convex Minimization AISTATS 2019
NAT: Neural Architecture Transformer for Accurate and Compact Architectures NIPS 2019
Hyperparameter Learning via Distributional Transfer NIPS 2019
Margin Learning Embedded Prediction for Video Anomaly Detection with A Few Anomalies IJCAI 2019
Graph Convolutional Networks for Temporal Action Localization ICCV 2019
Decentralized Optimization with Edge Sampling IJCAI 2019
Confidence Weighted Multitask Learning AAAI 2019
Bandit Online Learning on Graphs via Adaptive Optimization IJCAI 2018
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication ICML 2018
High-dimensional Similarity Learning via Dual-sparse Random Projection IJCAI 2018
Online Multitask Relative Similarity Learning IJCAI 2017
Locally Linear Factorization Machines IJCAI 2017
Learning User Dependencies for Recommendation IJCAI 2017
Projection-free Distributed Online Learning in Networks ICML 2017
Large Scale Online Kernel Learning JMLR 2016
Deceptive Review Spam Detection via Exploiting Task Relatedness and Unlabeled Data EMNLP 2016
Cost Sensitive Online Multiple Kernel Classification ACML 2016
Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization ICML 2016
A Boosting Algorithm for Item Recommendation with Implicit Feedback IJCAI 2015
Stochastic Optimization with Importance Sampling for Regularized Loss Minimization ICML 2015
Adaptive Stochastic Alternating Direction Method of Multipliers ICML 2015
Online Learning to Rank for Content-Based Image Retrieval IJCAI 2015
LIBOL: A Library for Online Learning Algorithms JMLR 2014
Online Passive Aggressive Active Learning and Its Applications ACML 2014
Large Scale Online Kernel Classification IJCAI 2013
Confidence Weighted Mean Reversion Strategy for On-Line Portfolio Selection AISTATS 2011
Double Updating Online Learning JMLR 2011
DUOL: A Double Updating Approach for Online Learning NIPS 2009