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Linking Objects in Videos by Importance Sampling

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Linking Objects in Videos by Importance Sampling

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On Vacuous and Non-Vacuous Generalization Bounds for Deep Neural Networks.

Bayesian regression explains how human participants handle parameter uncertainty

Collaborative Sampling in Generative Adversarial Networks

An Inertial Parallel and Asynchronous Forward-Backward Iteration for Distributed Convex Optimization

Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

Bayesian adaptation of chaos representations using variational inference and sampling on geodesics

Mirrored Langevin Dynamics

Mirrored Langevin Dynamics

Bayesian Calibration of Thermal-Hydraulics Model with Time-Dependent Output

Differential Privacy with Bounded Priors: Reconciling Utility and Privacy in Genome-Wide Association Studies

On Vacuous and Non-Vacuous Generalization Bounds for Deep Neural Networks.

Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

Bayesian regression explains how human participants handle parameter uncertainty

Bayesian adaptation of chaos representations using variational inference and sampling on geodesics

Bayesian Calibration of Thermal-Hydraulics Model with Time-Dependent Output

Collaborative Sampling in Generative Adversarial Networks

Mirrored Langevin Dynamics

Differential Privacy with Bounded Priors: Reconciling Utility and Privacy in Genome-Wide Association Studies

An Inertial Parallel and Asynchronous Forward-Backward Iteration for Distributed Convex Optimization

Mirrored Langevin Dynamics