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Concept

Boltzmann machine

Related publications (27)

PROFACTORY: Improving IoT Security via Formalized Protocol Customization

Mathias Josef Payer

As IoT applications gain widespread adoption, it becomes important to design and implement IoT protocols with security. Existing research in protocol security reveals that the majority of disclosed protocol vulnerabilities are caused by incorrectly impleme ...

USENIX ASSOC2022

Discriminative clustering with representation learning with any ratio of labeled to unlabeled data

Corinne Louise Jones

We present a discriminative clustering approach in which the feature representation can be learned from data and moreover leverage labeled data. Representation learning can give a similarity-based clustering method the ability to automatically adapt to an ...

2022

Fermionic wave functions from neural-network constrained hidden states

Giuseppe Carleo

We introduce a systematically improvable family of variational wave functions for the simulation of strongly correlated fermionic systems. This family consists of Slater determinants in an augmented Hilbert space involving “hidden” additional fermionic deg ...

2022

Deep Boltzmann Machines: Rigorous Results at Arbitrary Depth

Emanuele Mingione, Diego Alberici

A class of deep Boltzmann machines is considered in the simplified framework of a quenched system with Gaussian noise and independent entries. The quenched pressure of a K-layers spin glass model is studied allowing interactions only among consecutive laye ...

2021

The Solution of the Deep Boltzmann Machine on the Nishimori Line

Emanuele Mingione, Diego Alberici

The deep Boltzmann machine on the Nishimori line with a finite number of layers is exactly solved by a theorem that expresses its pressure through a finite dimensional variational problem of min-max type. In the absence of magnetic fields the order paramet ...

SPRINGER2021

Defect segmentation for multi-illumination quality control systems

Pascal Fua, Engin Türetken, Siavash Arjomand Bigdeli, David Honzátko

Thanks to recent advancements in image processing and deep learning techniques, visual surface inspection in production lines has become an automated process as long as all the defects are visible in a single or a few images. However, it is often necessary ...

2021

Robustness via Cross-Domain Ensembles

Amir Roshan Zamir, Shuqing Teresa Yeo, Oguzhan Fatih Kar

We present a method for making neural network predictions robust to shifts from the training data distribution. The proposed method is based on making predictions via a diverse set of cues (called 'middle domains') and ensembling them into one strong predi ...

IEEE2021