See my Google Scholar profile.


  1. Acerbi, L. (2020). Variational Bayesian Monte Carlo with Noisy Likelihoods. arXiv preprint. (linkcode)
  2. van Opheusden, B.*, Acerbi, L.* & Ma, W. J. (2020). Unbiased and Efficient Log-Likelihood Estimation with Inverse Binomial Sampling. arXiv preprint. (* equal contribution; link, code)
  3. Zhou, Y.*, Acerbi, L.* & Ma, W. J. (2019) The Role of Sensory Uncertainty in Simple Contour Integration, biorXiv preprint. (*equal contribution; link, code)

Journal articles and peer-reviewed proceedings

  1. Norton, E. H., Acerbi, L., Ma, W. J. & Landy M. S. (2019) Human online adaptation to changes in prior probability. PLoS Computational Biology 15(7): e1006681. (link, code)
  2. Acerbi, L. (2019). An Exploration of Acquisition and Mean Functions in Variational Bayesian Monte Carlo. In Proc. Machine Learning Research 96: 1-10. 1st Symposium on Advances in Approximate Bayesian Inference, Montréal, Canada. (link).
  3. Acerbi, L. (2018). Variational Bayesian Monte Carlo. In Proc. Advances in Neural Information Processing Systems 31 (NeurIPS ’18), Montréal, Canada. (linkarXiv, code).
  4. Acerbi*, L., Dokka*, K., Angelaki, D. E. & Ma, W. J. (2018) Bayesian comparison of explicit and implicit causal inference strategies in multisensory heading perception, PLoS Computational Biology 14(7): e1006110. (*equal contribution; link, code)
  5. Acerbi, L. & Ma, W. J. (2017). Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search. In Proc. Advances in Neural Information Processing Systems 30 (NeurIPS ’17), Long Beach, USA. (linkarXiv, codeposter).
  6. Acerbi, L., Vijayakumar, S. & Wolpert, D. M. (2017). Target Uncertainty Mediates Sensorimotor Error Correction, PLoS ONE 12(1): e0170466(link, article, article+supp, data)
  7. Acerbi, L., Ma, W. J. & Vijayakumar, S. (2014). A Framework for Testing Identifiability of Bayesian Models of Perception, In Proc. Advances in Neural Information Processing Systems (NeurIPS ’14), Montreal, Canada(articlesupp)
  8. Acerbi, L., Vijayakumar, S. & Wolpert, D. M. (2014). On the Origins of Suboptimality in Human Probabilistic Inference, PLoS Computational Biology 10(6): e1003661. (linkarticlearticle+supp, data)
  9. Acerbi L., Wolpert D.M. & Vijayakumar S. (2012). Internal Representations of Temporal Statistics and Feedback Calibrate Motor-Sensory Interval Timing, PLoS Computational Biology 8(11): e1002771. (link, article, article+supp, data)
  10. Acerbi L., Dennunzio A. & Formenti E. (2013). Surjective multidimensional cellular automata are non-wandering: A combinatorial proof, Information Processing Letters 113(5-6): 156-159. (link)
  11. Acerbi L., Dennunzio A. & Formenti E. (2009). Conservation of Some Dynamical Properties of Operations on Cellular Automata, Theoretical Computer Science, 410(38-40): 3685-3693. (link)
  12. Acerbi L., Dennunzio A. & Formenti E. (2007). Shifting and Lifting of Cellular Automata, in Proc. Third Conference on Computability in Europe, CiE 2007: 1-10; June 2007. (link)


  1. Acerbi, L. (2015) Complex internal representations in sensorimotor decision making: a Bayesian investigation. Doctoral dissertation, The University of Edinburgh. Advisors: Prof. Sethu Vijayakumar, Prof. Daniel M. Wolpert. (link, thesis)