| 2025 | CIKM | Learning Optimal Personalised Reservation Prices in Impression Ad Auctions with Mixture Density Networks. | Dmitrii Moor, Emma Zetterdahl, Paul van Vliet, Zhenwen Dai, Mounia Lalmas |
| 2025 | KDD | Optimising Budget Management via Primal-Dual Approximation with Constrained Polynomial Weights Update. | Dmitrii Moor, Per Berglund, Hannes Karlbom, Zhenwen Dai, Kyle Kretschman, Mounia Lalmas |
| 2025 | RecSys | Prompt-to-Slate: Diffusion Models for Prompt-Conditioned Slate Generation. | Federico Tomasi, Francesco Fabbri, Justin Carter, Elias Kalomiris, Mounia Lalmas, Zhenwen Dai |
| 2024 | ICLR | In-context Exploration-Exploitation for Reinforcement Learning. | Zhenwen Dai, Federico Tomasi, Sina Ghiassian |
| 2023 | AISTATS | The ELBO of Variational Autoencoders Converges to a Sum of Entropies. | Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jrg Lcke |
| 2023 | CIKM | Exploiting Sequential Music Preferences via Optimisation-Based Sequencing. | Dmitrii Moor, Yi Yuan, Rishabh Mehrotra, Zhenwen Dai, Mounia Lalmas |
| 2023 | KDD | Automatic Music Playlist Generation via Simulation-based Reinforcement Learning. | Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai |
| 2022 | UAI | Efficient inference for dynamic topic modeling with large vocabularies. | Federico Tomasi, Mounia Lalmas, Zhenwen Dai |
| 2021 | ICML | Black-box density function estimation using recursive partitioning. | Erik Bodin, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek |
| 2020 | ICML | Modulating Surrogates for Bayesian Optimization. | Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek |
| 2020 | UAI | Stochastic Variational Inference for Dynamic Correlated Topic Models. | Federico Tomasi, Praveen Chandar, Gal Levy-Fix, Mounia Lalmas-Roelleke, Zhenwen Dai |
| 2019 | CVPR | Variational Information Distillation for Knowledge Transfer. | Sungsoo Ahn, Shell Xu Hu, Andreas C. Damianou, Neil D. Lawrence, Zhenwen Dai |
| 2018 | ICML | Structured Variationally Auto-encoded Optimization. | Xiaoyu Lu, Javier Gonzlez, Zhenwen Dai, Neil D. Lawrence |
| 2017 | ICML | Preferential Bayesian Optimization. | Javier Gonzlez, Zhenwen Dai, Andreas C. Damianou, Neil D. Lawrence |
| 2016 | AISTATS | Batch Bayesian Optimization via Local Penalization. | Javier Gonzlez, Zhenwen Dai, Philipp Hennig, Neil D. Lawrence |
| 2012 | CVPR | Unsupervised learning of translation invariant occlusive components. | Zhenwen Dai, Jrg Lcke |
| 2012 | CVPR | Autonomous cleaning of corrupted scanned documents - A generative modeling approach. | Zhenwen Dai, Jrg Lcke |
| 2011 | ICCV | Pose estimation from reflections for specular surface recovery. | Miaomiao Liu, Kwan-Yee Kenneth Wong, Zhenwen Dai, Zhihu Chen |
| 2010 | ACCV | Specular Surface Recovery from Reflections of a Planar Pattern Undergoing an Unknown Pure Translation. | Miaomiao Liu, Kwan-Yee Kenneth Wong, Zhenwen Dai, Zhihu Chen |
| 2009 | ACCV | Polygonal Light Source Estimation. | Dirk Schnieders, Kwan-Yee Kenneth Wong, Zhenwen Dai |
| 2007 | PAKDD | Understanding Research Field Evolving and Trend with Dynamic Bayesian Networks. | Jinlong Wang, Congfu Xu, Gang Li, Zhenwen Dai, Guojing Luo |