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Xingchen Wan
Xingchen Wan
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Title
Cited by
Cited by
Year
Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels
B Ru*, X Wan*, X Dong, M Osborne
International Conference on Learning Representations (ICLR) 9, 2021
1102021
Sentiment Correlation in Financial News Networks and Associated Market Movements
X Wan*, J Yang*, S Marinov, JP Calliess, S Zohren, X Dong
Scientific Reports 11 (3062), 2021
652021
Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces
X Wan, V Nguyen, H Ha, B Ru, C Lu, MA Osborne
International Conference on Machine Learning (ICML) 38, 10663-10674, 2021
582021
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
S Daulton, X Wan, D Eriksson, M Balandat, MA Osborne, E Bakshy
Advances in Neural Information Processing Systems (NeurIPS) 35, 2022
332022
BOiLS: Bayesian Optimisation for Logic Synthesis
A Grosnit*, C Malherbe*, R Tutunov, X Wan, J Wang, HB Ammar
Design, Automation & Test in Europe Conference (DATE) 25, 2022
31*2022
Adversarial Attacks on Graph Classifiers via Bayesian Optimisation
X Wan, H Kenlay, B Ru, A Blaas, M Osborne, X Dong
Advances in Neural Information Processing Systems (NeurIPS) 34, 2021
30*2021
Better Zero-Shot Reasoning with Self-Adaptive Prompting
X Wan, R Sun, H Dai, SO Arik, T Pfister
Findings of the Association for Computational Linguistics: ACL 2023, 2023
252023
AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning
H Zhou*, X Wan*, I Vulić, A Korhonen
Transactions of the Association for Computational Linguistics (TACL) 12, 525–542, 2024
222024
On Redundancy and Diversity in Cell-based Neural Architecture Search
X Wan, B Ru, PM Esperanša, Z Li
International Conference on Learning Representations (ICLR) 10, 2022
212022
Bayesian Generational Population-Based Training
X Wan, C Lu, J Parker-Holder, PJ Ball, V Nguyen, B Ru, M Osborne
International Conference on Automated Machine Learning (AutoML-Conf) 1, 14/1-27, 2022
202022
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering
H Zhou, X Wan, L Proleev, D Mincu, J Chen, K Heller, S Roy
International Conference on Learning Representations (ICLR) 12, 2024
182024
Deep Curvature Suite
D Granziol, X Wan, T Garipov
arXiv preprint arXiv:1912.09656, 2019
18*2019
Iterate Averaging in the Quest for Best Test Error
D Granziol*, N Baskerville*, X Wan*, S Albanie, S Roberts
Journal of Machine Learning Research (JMLR) 25, 2024
16*2024
Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and Pruning
H Zhou*, X Wan*, I Vulić, A Korhonen
Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
112023
Universal Self-Adaptive Prompting
X Wan, R Sun, H Nakhost, H Dai, JM Eisenschlos, SO Arik, T Pfister
Empirical Methods in Natural Language Processing (EMNLP), 2023
102023
Approximate Neural Architecture Search via Operation Distribution Learning
X Wan, B Ru, PM Esperanša, FM Carlucci
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2377-2386, 2022
92022
Adaptive Batch Sizes for Active Learning A Probabilistic Numerics Approach
M Adachi, S Hayakawa, M J°rgensen, X Wan, V Nguyen, H Oberhauser, ...
International Conference on Artificial Intelligence and Statistics (AISTATS) 27, 2024
4*2024
Explaining the Adaptive Generalisation Gap
D Granziol, N Baskerville, X Wan, S Albanie, S Roberts
arXiv preprint arXiv:2011.08181v4, 2020
42020
Bayesian Optimisation of Functions on Graphs
X Wan*, P Osselin*, H Kenlay, B Ru, MA Osborne, X Dong
Advances in Neural Information Processing Systems (NeurIPS) 36, 2023
3*2023
Working Memory Capacity of ChatGPT: An Empirical Study
D Gong, X Wan, D Wang
AAAI Conference on Artificial Intelligence (AAAI) 38, 2024
22024
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