| 2023 | Incentivising Diffusion while Preserving Differential Privacy. | Fengjuan Jia, Mengxiao Zhang, Jiamou Liu, Bakh Khoussainov |
| 2023 | Content Sharing Design for Social Welfare in Networked Disclosure Game. | Feiran Jia, Chenxi Qiu, Sarah Rajtmajer, Anna Cinzia Squicciarini |
| 2023 | Bayesian inference for vertex-series-parallel partial orders. | Chuxuan Jiang, Geoff K. Nicholls, Jeong-Eun (Kate) Lee |
| 2023 | Multi-view graph contrastive learning for solving vehicle routing problems. | Yuan Jiang, Zhiguang Cao, Yaoxin Wu, Jie Zhang |
| 2023 | Noisy adversarial representation learning for effective and efficient image obfuscation. | Jonghu Jeong, Minyong Cho, Philipp Benz, Tae-Hoon Kim |
| 2023 | Robust statistical comparison of random variables with locally varying scale of measurement. | Christoph Jansen, Georg Schollmeyer, Hannah Blocher, Julian Rodemann, Thomas Augustin |
| 2023 | Investigating a Generalization of Probabilistic Material Implication and Bayesian Conditionals. | Michael Jahn, Matthias Scheutz |
| 2023 | Posterior sampling-based online learning for the stochastic shortest path model. | Mehdi Jafarnia-Jahromi, Liyu Chen, Rahul Jain, Haipeng Luo |
| 2023 | Optimistic Thompson Sampling-based algorithms for episodic reinforcement learning. | Bingshan Hu, Tianyue H. Zhang, Nidhi Hegde, Mark Schmidt |
| 2023 | ASTRA: Understanding the practical impact of robustness for probabilistic programs. | Zixin Huang, Saikat Dutta, Sasa Misailovic |
| 2023 | Increasing effect sizes of pairwise conditional independence tests between random vectors. | Tom Hochsprung, Jonas Wahl, Andreas Gerhardus, Urmi Ninad, Jakob Runge |
| 2023 | Loosely consistent emphatic temporal-difference learning. | Jiamin He, Fengdi Che, Yi Wan, A. Rupam Mahmood |
| 2023 | Massively parallel reweighted wake-sleep. | Thomas Heap, Gavin Leech, Laurence Aitchison |
| 2023 | Scalable and robust tensor ring decomposition for large-scale data. | Yicong He, George K. Atia |
| 2023 | Inference and sampling of point processes from diffusion excursions. | Ali Hasan, Yu Chen, Yuting Ng, Mohamed Abdelghani, Anderson Schneider, Vahid Tarokh |
| 2023 | On inference and learning with probabilistic generating circuits. | Juha Harviainen, Vaidyanathan Peruvemba Ramaswamy, Mikko Koivisto |
| 2023 | Revisiting Bayesian network learning with small vertex cover. | Juha Harviainen, Mikko Koivisto |
| 2023 | On the Convergence of Continual Learning with Adaptive Methods. | Seungyub Han, Yeongmo Kim, Taehyun Cho, Jungwoo Lee |
| 2023 | Differentiable user models. | Alex Hmlinen, Mustafa Mert elikok, Samuel Kaski |
| 2023 | Interpretable differencing of machine learning models. | Swagatam Haldar, Diptikalyan Saha, Dennis Wei, Rahul Nair, Elizabeth M. Daly |
| 2023 | Sufficient identification conditions and semiparametric estimation under missing not at random mechanisms. | Anna Guo, Jiwei Zhao, Razieh Nabi |
| 2023 | Causal Discovery for time series from multiple datasets with latent contexts. | Wiebke Gnther, Urmi Ninad, Jakob Runge |
| 2023 | Functional causal Bayesian optimization. | Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa |
| 2023 | Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation via Energy-Based Normalizing Flow. | Denis A. Gudovskiy, Tomoyuki Okuno, Yohei Nakata |
| 2023 | Stochastic Graphical Bandits with Heavy-Tailed Rewards. | Yutian Gou, Jinfeng Yi, Lijun Zhang |