Results 51 to 60 of about 425,037 (266)

Automatic Variational Inference in Stan [PDF]

, 2015
Variational inference is a scalable technique for approximate Bayesian inference. Deriving variational inference algorithms requires tedious model-specific calculations; this makes it difficult to automate.
Blei, David M., Gelman, Andrew, Kucukelbir, Alp, Ranganath, Rajesh   +3 more
core  

Accelerated Parallel Non-conjugate Sampling for Bayesian Non-parametric Models

, 2019
Inference of latent feature models in the Bayesian nonparametric setting is generally difficult, especially in high dimensional settings, because it usually requires proposing features from some prior distribution. In special cases, where the integration
Perez-Cruz, Fernando, Williamson, Sinead A., Zhang, Michael Minyi   +2 more
core   +1 more source

Superionic Amorphous Li2ZrCl6 and Li2HfCl6

Advanced Materials, EarlyView.
Amorphous Li2HfCl6 and L2ZrCl6 are shown to be promising solid‐state electrolytes with predicted ionic conductivities >20 mS·cm−1. Molecular dynamics simulations with machine‐learning force fields reveal that anion vibrations and flexible MCl6 octahedra soften the Li coordination cage and enhance mobility. Correlation between Li‐ion diffusivity and the
Shukai Yao, De‐en Jiang
wiley   +1 more source

Causal inference with large-scale assessments in education from a Bayesian perspective: a review and synthesis

Large-scale Assessments in Education, 2016
This paper reviews recent research on causal inference with large-scale assessments in education from a Bayesian perspective. I begin by adopting the potential outcomes model of Rubin (J Educ Psychol 66:688-701, 1974) as a framework for causal inference ...
David Kaplan
doaj   +1 more source

The Size-Weight Illusion is not anti-Bayesian after all: a unifying Bayesian account [PDF]

PeerJ, 2016
When we lift two differently-sized but equally-weighted objects, we expect the larger to be heavier, but the smaller feels heavier. However, traditional Bayesian approaches with “larger is heavier” priors predict the smaller object should feel lighter ...
Megan A.K. Peters, Wei Ji Ma, Ladan Shams   +2 more
doaj   +2 more sources

Towards modelling active sound localisation based on Bayesian inference in a static environment

Acta Acustica, 2021
Over the decades, Bayesian statistical inference has become a staple technique for modelling human multisensory perception. Many studies have successfully shown how sensory and prior information can be combined to optimally interpret our environment ...
McLachlan Glen, Majdak Piotr, Reijniers Jonas, Peremans Herbert   +3 more
doaj   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Fuzzy Bayesian inference for under-five mortality data

Franklin Open
Under-five mortality remains a significant global health challenge, with millions of children dying before their fifth birthday each year. This study explores the application of fuzzy Bayesian inference for under-five mortality data using Tanzania as a ...
M.K. Mwanga, S.S. Mirau, J.M. Tchuenche, I.S. Mbalawata   +3 more
doaj   +1 more source

Consensus Formation and Change are Enhanced by Neutrality

Advanced Science, EarlyView.
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag, Janina A. Hoffmann, Tim Rogers, Christian A. Yates   +3 more
wiley   +1 more source

Hierarchical Summary Statistics Encoding Across Primary Visual and Posterior Parietal Cortices

Advanced Science, EarlyView.
This study shows that mouse V1 simultaneously encodes the ensemble mean and variance of motion, providing a robust summary‐statistic representation that persists despite single‐neuron variability. These signals propagate to PPC, where they are transformed into abstract category representations during decision making.
Young‐Beom Lee, Oliver James, Gaeun Jung, Doyun Lee, Yee‐Joon Kim   +4 more
wiley   +1 more source