Zhengyang Zhou
24 papers · 2020–2026 · 6 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (5) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (5) π Cross-Pollinator (14)
π
Renaissance Researcher
(8)
πΊοΈ
Taxonomy Completionist
(49)
π
Interdisciplinary Bridge
π€
Dynamic Duo
(17)
π
Keyword Champion
(3)
π
Grand Slam
β‘
Prolific Year
(10)
π
Century Club
(20)
ποΈ
Keyword Collector
(99)
Conferences
AAAI (9)
IJCAI (5)
ICML (4)
NIPS (4)
ACL (1)
ICLR (1)
Top co-authors
Keywords
graph neural network
(8)
causal inference
(5)
dynamic graph
(4)
time series forecasting
(3)
representation learning
(3)
causal learning
(3)
information theory
(2)
multi-task learning
(2)
domain generalization
(2)
traffic prediction
(2)
time series prediction
(2)
large language model
(2)
graph representation learning
(1)
knowledge transfer
(1)
graph classification
(1)
domain adaptation
(1)
few-shot learning
(1)
spatio-temporal modeling
(1)
transfer learning
(1)
prompt learning
(1)
Papers
MSAnchor: De Novo Molecular Generation from Mass Spectrometry Data with Anchor-Extended Molecular Scaffolds
AAAI 2026
Augur: Modeling Covariate Causal Associations in Time Series via Large Language Models
ACL 2026
Talk2Image: A Multi-Agent System for Multi-Turn Image Generation and Editing
AAAI 2026
U2B: Scale-unbiased Representation Converter for Graph Classification with Imbalanced and Balanced Scale Distributions
AAAI 2026
SynEVO: A neuro-inspired spatiotemporal evolutional framework for cross-domain adaptation
ICML 2025
TimeBase: The Power of Minimalism in Efficient Long-term Time Series Forecasting
ICML 2025
Robust Spatio-Temporal Centralized Interaction for OOD Learning
ICML 2025
Enhancing Graph Invariant Learning from a Negative Inference Perspective
ICML 2025
Causal Learning Meet Covariates: Empowering Lightweight and Effective Nationwide Air Quality Forecasting
IJCAI 2025
Revealing Concept Shift in Spatio-Temporal Graphs via State Learning
IJCAI 2025
A Twist for Graph Classification: Optimizing Causal Information Flow in Graph Neural Networks
AAAI 2024
NondBREM: Nondeterministic Offline Reinforcement Learning for Large-Scale Order Dispatching
AAAI 2024
Towards Dynamic Spatial-Temporal Graph Learning: A Decoupled Perspective
AAAI 2024
HDMixer: Hierarchical Dependency with Extendable Patch for Multivariate Time Series Forecasting
AAAI 2024
Earthfarsser: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model
AAAI 2024
Get Rid of Isolation: A Continuous Multi-task Spatio-Temporal Learning Framework
NIPS 2024
Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning
IJCAI 2024
Make Bricks with a Little Straw: Large-Scale Spatio-Temporal Graph Learning with Restricted GPU-Memory Capacity
IJCAI 2024
LeRet: Language-Empowered Retentive Network for Time Series Forecasting
IJCAI 2024
Improving Generalization of Dynamic Graph Learning via Environment Prompt
NIPS 2024
CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement
NIPS 2023
Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment
NIPS 2023
GReTo: Remedying dynamic graph topology-task discordance via target homophily
ICLR 2023
RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework
AAAI 2020