Concept

Black box

Related publications (16)

Towards Trustworthy Deep Learning for Image Reconstruction

The remarkable ability of deep learning (DL) models to approximate high-dimensional functions from samples has sparked a revolution across numerous scientific and industrial domains that cannot be overemphasized. In sensitive applications, the good perform ...

EPFL2024

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

Yi Zhang, Wenlong Liao, Zhe Yang

Recently, remarkable progress has been made in the application of machine learning (ML) techniques (e.g., neural networks) to transformer fault diagnosis. However, the diagnostic processes employed by these techniques often suffer from a lack of interpreta ...

Piscataway2024

The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations

Vinitra Swamy, Jibril Albachir Frej

Explainable Artificial Intelligence (XAI) plays a crucial role in enabling human understanding and trust in deep learning systems, often defined as determining which features are most important to a model's prediction. As models get larger, more ubiquitous ...

2023

Zero-Knowledge IOPs with Linear-Time Prover and Polylogarithmic-Time Verifier

Alessandro Chiesa, Siqi Liu

Interactive oracle proofs (IOPs) are a multi-round generalization of probabilistically checkable proofs that play a fundamental role in the construction of efficient cryptographic proofs. We present an IOP that simultaneously achieves the properties of zer ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Introducing reinforcement learning to the energy system design process

Jean-Louis Scartezzini, Amarasinghage Tharindu Dasun Perera, Vahid Moussavi Nik

Design optimization of distributed energy systems has become an interest of a wider group of researchers due the capability of these systems to integrate non-dispatchable renewable energy technologies such as solar PV and wind. White box models, using line ...

2020

Modeling and Assessment of Urban Energy Systems

Amarasinghage Tharindu Dasun Perera

Improving the energy sustainability of our cities involves the integration of multiple renewable energy technologies into existing energy infrastructure, stretching the capabilities of traditional energy systems to the limit. To consider the transition tak ...

EPFL2019

A Tight Lower Bound for Entropy Flattening

Mika Tapani Göös, Jiapeng Zhang

We study entropy flattening: Given a circuit C_X implicitly describing an n-bit source X (namely, X is the output of C_X on a uniform random input), construct another circuit C_Y describing a source Y such that (1) source Y is nearly flat (uniform on its s ...

Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Wadern/Saarbruecken, Germany2018

An artificial neural network as a troubled-cell indicator

Jan Sickmann Hesthaven, Deep Ray

High-resolution schemes for conservation laws need to suitably limit the numerical solution near discontinuities, in order to avoid Gibbs oscillations. The solution quality and the computational cost of such schemes strongly depend on their ability to corr ...

2018

Shape constrained splines as transparent black-box models for bioprocess modeling

Dominique Bonvin, Julien Léo Billeter, Sriniketh Srinivasan

Empirical model identification for biological systems is a challenging task due to the combined effects of complex interactions, nonlinear effects, and lack of specific measurements. In this context, several researchers have provided tools for experimental ...

Elsevier2017

A Systemic Approach to Multi-Party Relationship Modeling

Alain Wegmann, Anshuman Bahadur Saxena

Socio-economic systems exist in a wide variety of activity domains and are composed of multiple stakeholder groups. These groups pursue objectives which are often entirely motivated from within their local context. Domain specificities in the form of insti ...

2012

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