Luigi Acerbi
Luigi Acerbi
Assistant Professor of Machine and Human Intelligence, University of Helsinki
Verified email at helsinki.fi - Homepage
Title
Cited by
Cited by
Year
On the Origins of Suboptimality in Human Probabilistic Inference
L Acerbi, S Vijayakumar, DM Wolpert
PLOS Computational Biology 10 (6), e1003661, 2014
1652014
Internal Representations of Temporal Statistics and Feedback Calibrate Motor-Sensory Interval Timing
L Acerbi, DM Wolpert, S Vijayakumar
PLoS computational biology 8 (11), e1002771, 2012
1512012
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search
L Acerbi, WJ Ma
Advances in Neural Information Processing Systems, 1834-1844, 2017
1192017
Conservation of some dynamical properties for operations on cellular automata
L Acerbi, A Dennunzio, E Formenti
Theoretical Computer Science 410 (38-40), 3685-3693, 2009
522009
A Framework for Testing Identifiability of Bayesian Models of Perception
L Acerbi, WJ Ma, S Vijayakumar
Advances in Neural Information Processing Systems, 1026-1034, 2014
512014
Bayesian comparison of explicit and implicit causal inference strategies in multisensory heading perception
L Acerbi*, K Dokka*, DE Angelaki, WJ Ma
PLOS Computational Biology 14 (7), e1006110, 2018
422018
Variational Bayesian Monte Carlo
L Acerbi
Advances in Neural Information Processing Systems, 8223-8233, 2018
232018
Shifting and lifting of cellular automata
L Acerbi, A Dennunzio, E Formenti
Computation and Logic in the Real World, 1-10, 2007
222007
Human online adaptation to changes in prior probability
EH Norton, L Acerbi, WJ Ma, MS Landy
PLOS Computational Biology 15 (7), e1006681, 2019
162019
Target Uncertainty Mediates Sensorimotor Error Correction
L Acerbi, S Vijayakumar, DM Wolpert
PLOS ONE 12 (1), e0170466, 2017
152017
Surjective multidimensional cellular automata are non-wandering: A combinatorial proof
L Acerbi, A Dennunzio, E Formenti
Information Processing Letters 113 (5-6), 156-159, 2013
122013
Unbiased and efficient log-likelihood estimation with inverse binomial sampling
B van Opheusden*, L Acerbi*, WJ Ma
PLOS Computational Biology 16 (12), e1008483, 2020
72020
Variational Bayesian Monte Carlo with Noisy Likelihoods
L Acerbi
Advances in Neural Information Processing Systems 33, 2020
52020
An Exploration of Acquisition and Mean Functions in Variational Bayesian Monte Carlo
L Acerbi
Symposium on Advances in Approximate Bayesian Inference, 1-10, 2019
52019
The role of sensory uncertainty in simple contour integration
Y Zhou*, L Acerbi*, WJ Ma
PLoS Computational Biology, 2020 16 (11), e1006308, 2020
4*2020
Uncertainty is Maintained and Used in Working Memory
AH Yoo, L Acerbi, WJ Ma
bioRxiv, 2020
32020
Complex internal representations in sensorimotor decision making: a Bayesian investigation
L Acerbi
The University of Edinburgh, 2015
32015
Dynamic allocation of limited memory resources in reinforcement learning
N Patel, L Acerbi, A Pouget
Advances in Neural Information Processing Systems 33, 2020
22020
Optimality under fire: Dissociating learning from Bayesian integration
L Acerbi, B Marius’t Hart, FM Behbahani, MA Peters
Translational and Computational Motor Control (TCMC) satellite meeting atá…, 2013
12013
Approximate Inference through Sequential Measurements of Likelihoods Accounts for Hick's Law.
X Li, L Acerbi, WJ Ma
CogSci, 3510, 2019
2019
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