Publications
Smith, F. et al. (2023) “Prediction-Oriented Bayesian Active Learning”, in Proceedings of Machine Learning Research, pp. 7331–7348.
Campbell, A. et al. (2023) “Trans-Dimensional Generative Modeling via Jump Diffusion Models”, in Advances in Neural Information Processing Systems.
Xu, J. et al. (2023) “Deep Stochastic Processes via Functional Markov Transition Operators”, in Advances in Neural Information Processing Systems.
Sharma, M. et al. (2023) “Do Bayesian Neural Networks Need To Be Fully Stochastic?”, in Proceedings of Machine Learning Research, pp. 7694–7722.
Ivanova, D. et al. (2023) “CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design”, in Proceedings of Machine Learning Research, pp. 14445–14464.
Miao, N. et al. (2023) “Learning Instance-Specific Augmentations by Capturing Local Invariances”, in Proceedings of Machine Learning Research, pp. 24720–24736.
Zaidi, S. et al. (2023) “When Does Re-initialization Work?”, in Proceedings of Machine Learning Research, pp. 12–26.
Miao, N. et al. (2023) “Learning Instance-Specific Augmentations by Capturing Local Invariances”, in Proceedings of Machine Learning Research, pp. 24720–24736.
Ghalebikesabi, S. et al. (2023) “Quasi-Bayesian Nonparametric Density Estimation via Autoregressive Predictive Updates”, in Proceedings of Machine Learning Research, pp. 658–668.