On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,291 papers · 148 categories

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6 results for “Variational-Laplace”

Variational Laplace for Bayesian neural networksstat.ML

Variational Laplace improves Bayesian neural networks performance.

problem Improving Bayesian neural networks performance.

method Develops variational Laplace for BNNs, exploiting curvature of likelihood.

result Variational Laplace outperforms other inference methods.

Bayesian neural networks Variational Laplace ELBO Curvature Weight-decay

2021-02-27abs ↗pdf ↗

Variational Laplace for Bayesian neural networksstat.ML

Variational Laplace improves Bayesian neural network performance without sampling.

problem Improving Bayesian neural network performance and calibration.

method Develops a new variational Laplace method for BNNs, exploiting curvature of likelihood.

result Variational Laplace outperforms standard VI methods in test performance and calibration.

Bayesian neural networks Variational Laplace ELBO Weight-decay Squared-gradient regularizer

2020-11-20abs ↗pdf ↗

The variational Laplace approach to approximate Bayesian inferencestat.ME

Efficient Bayesian inference via Gaussian approximations.

problem Parameter estimation and model selection in Bayesian statistics.

method Variational-Laplace approach using Gaussian approximations.

result Novel theoretical results on asymptotic convergence of VL schemes.

Bayesian inference Gaussian approximations Variational-Laplace Asymptotic convergence Hierarchical models

2017-03-02abs ↗pdf ↗

On parameters transformations for emulating sparse priors using variational-Laplace inferencestat.ML

Proposes a method to emulate sparse priors using L1 regularization without complex transformations.

problem Sparse priors in under-determined estimation problems.

method Parameter transform to emulate sparse priors under L2 regularization.

result L1 regularization can be achieved with a remapping of parameters under normal priors.

sparse priors L1 regularization L2 regularization variational-Laplace inference Monte-Carlo simulations

2017-03-06abs ↗pdf ↗

Bayesian Belief Updating of Spatiotemporal Seizure Dynamicsstat.ML

Bayesian method models spatiotemporal seizure dynamics.

problem Understanding complex seizure dynamics in space and time.

method Bayesian belief updating using variational Laplace in DCM framework.

result Framework assimilates spatial and temporal seizure dynamics.

epilepsy seizure dynamics Bayesian updating spatiotemporal analysis partial differential equation

2017-05-20abs ↗pdf ↗

Unifying and generalizing models of neural dynamics during decision-makingq-bio.NC

Unified framework models neural decision-making, improving accuracy.

problem Limitations in modeling neural activity during decision-making.

method Unifying framework based on state-space models with scalable inference.

result Two-dimensional accumulator better captures neural responses.

decision-making neural dynamics state-space models variational inference spiking responses

2020-01-13abs ↗pdf ↗