| Doubly stochastic variational inference for neural processes with hierarchical latent variables Q Wang, H Van Hoof ICML 2020, 2020 | 45 | 2020 |
| Model-based meta reinforcement learning using graph structured surrogate models and amortized policy search Q Wang, H Van Hoof ICML 2022 Spotlight, 2022 | 25 | 2022 |
| Learning expressive meta-representations with mixture of expert neural processes Q Wang, H van Hoof NeurIPS 2022, 2022 | 19 | 2022 |
| Bridge the Inference Gaps of Neural Processes via Expectation Maximization Q Wang, M Federici, H van Hoof ICLR 2023, 2023 | 14 | 2023 |
| Episodic Multi-Task Learning with Heterogeneous Neural Processes J Shen, X Zhen, Q Wang, M Worring NeurIPS 2023 Spotlight, 2023 | 11 | 2023 |
| Large-scale generative simulation artificial intelligence: The next hotspot Q Wang, Y Feng, J Huang, Y Lv, Z Xie, X Gao The Innovation 4 (6), 2023 | 9 | 2023 |
| A simple yet effective strategy to robustify the meta learning paradigm Q Wang, Y Lv, Y Feng, Z Xie, J Huang NeurIPS 2023, 2024 | 8 | 2024 |
| Offline Reinforcement Learning with OOD State Correction and OOD Action Suppression Y Mao, Q Wang, C Chen, Y Qu, X Ji NeurIPS 2024, 2024 | 4 | 2024 |
| Robust Fast Adaptation from Adversarially Explicit Task Distribution Generation Q Wang, Y Lv, Y Mao, Y Qu, Y Xu, X Ji KDD 2025, 2024 | 3 | 2024 |
| Choices are More Important than Efforts: LLM Enables Efficient Multi-Agent Exploration Y Qu, B Wang, Y Jiang, J Shao, Y Mao, Q Wang, C Liu, X Ji arXiv preprint arXiv:2410.02511, 2024 | 3 | 2024 |
| Doubly Mild Generalization for Offline Reinforcement Learning Y Mao, Q Wang, Y Qu, Y Jiang, X Ji NeurIPS 2024, 2024 | 2 | 2024 |
| Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning Y Lv, Q Wang, D Liang, Z Xie NeurIPS 2024, 2024 | 1 | 2024 |
| GO4Align: Group Optimization for Multi-Task Alignment J Shen, Q Wang, Z Xiao, N Van Noord, M Worring NeurIPS 2024, 2024 | 1 | 2024 |
| Beyond Any-Shot Adaptation: Predicting Optimization Outcome for Robustness Gains without Extra Pay Q Wang, Z Xiao, Y Mao, Y Qu, J Shen, Y Lv, X Ji https://arxiv.org/abs/2501.11039, 2025 | | 2025 |
| DynaPrompt: Dynamic Test-Time Prompt Tuning Z Xiao, S Yan, J Hong, J Cai, X Jiang, Y Hu, J Shen, Q Wang, CGM Snoek ICLR 2025, 2025 | | 2025 |
| Functional representation learning for uncertainty quantification and fast skill transfer Q Wang, MW (Supervisor), HH (Supervisor) University of Amsterdam, PhD Thesis, 2025 | | 2025 |
| Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning Y Qu, Y Jiang, B Wang, Y Mao, Q Wang, C Liu, X Ji AAAI 2025, 2024 | | 2024 |
| Separable Mixture of Low-Rank Adaptation for Continual Visual Instruction Tuning Z Wang, C Che, Q Wang, Y Li, Z Shi, M Wang arXiv preprint arXiv:2411.13949, 2024 | | 2024 |
| Balanced Confidence Calibration for Graph Neural Networks H Yang, M Wang, Q Wang, M Lao, Y Zhou KDD 2024, 2024 | | 2024 |
| Reducing Fine-Tuning Memory Overhead by Approximate and Memory-Sharing Backpropagation Y Yang, Y Shi, Q Wang, X Zhen, Y Shi, J Xu ICML 2024, 2024 | | 2024 |
Herke van HoofUniversity of Amsterdam (UVA)Correu electrònic verificat a uva.nl
