| 2025 | AISTATS | Your Finetuned Large Language Model is Already a Powerful Out-of-distribution Detector. | Andi Zhang, Tim Z. Xiao, Weiyang Liu, Robert Bamler, Damon Wischik |
| 2025 | UAI | Well-Defined Function-Space Variational Inference in Bayesian Neural Networks via Regularized KL-Divergence. | Tristan Cinquin, Robert Bamler |
| 2024 | ICLR | Predictive, scalable and interpretable knowledge tracing on structured domains. | Hanqi Zhou, Robert Bamler, Charley M. Wu, lvaro Tejero-Cantero |
| 2024 | ICML | Differentiable Annealed Importance Sampling Minimizes The Jensen-Shannon Divergence Between Initial and Target Distribution. | Johannes Zenn, Robert Bamler |
| 2023 | ICLR | Trading Information between Latents in Hierarchical Variational Autoencoders. | Tim Z. Xiao, Robert Bamler |
| 2023 | ICLR | Resampling Gradients Vanish in Differentiable Sequential Monte Carlo Samplers. | Johannes Zenn, Robert Bamler |
| 2020 | ICLR | Extreme Classification via Adversarial Softmax Approximation. | Robert Bamler, Stephan Mandt |
| 2020 | ICML | Variational Bayesian Quantization. | Yibo Yang, Robert Bamler, Stephan Mandt |
| 2019 | UAI | Augmenting and Tuning Knowledge Graph Embeddings. | Robert Bamler, Farnood Salehi, Stephan Mandt |
| 2018 | ICML | Improving Optimization in Models With Continuous Symmetry Breaking. | Robert Bamler, Stephan Mandt |
| 2017 | ICML | Dynamic Word Embeddings. | Robert Bamler, Stephan Mandt |