Concept

Deductive-nomological model

Publications associées (8)

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

On Smoothed Explanations: Quality and Robustness

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Michail Vlachos, Ahmad Ajalloeian

Explanation methods highlight the importance of the input features in taking a predictive decision, and represent a solution to increase the transparency and trustworthiness in machine learning and deep neural networks (DNNs). However, explanation methods ...

New York2022

Empirical validation of MesoHABSIM models developed with different habitat suitability criteria for bullhead cottus gobio L. as an indicator species

Giovanni De Cesare, Mikolaj Stanislaw Adamczyk, Piotr Parasiewicz

Application of instream habitat models such as the Mesohabitat Simulation Model (MesoHABSIM) is becoming increasingly popular. Such models can predict alteration to a river physical habitat caused by hydropower operation or river training. They are a tool ...

2019

Are We Ready for Autonomous Drone Racing? The UZH-FPV Drone Racing Datase

Davide Scaramuzza, Titus Cieslewski

Despite impressive results in visual-inertial state estimation in recent years, high speed trajectories with six degree of freedom motion remain challenging for existing estimation algorithms. Aggressive trajectories feature large accelerations and rapid r ...

2019

On raw inertial measurements in dynamic networks

Jan Skaloud, Davide Antonio Cucci

Dynamic Networks have been introduced in the literature to solve multi-sensor fusion problems for navigation and mapping. They have been shown to outperform conventional methods in challenging scenarios, such as corridor mapping or self-calibration. In thi ...

2019

A Computational Approach for the Design of Epidural Electrical Spinal Cord Stimulation Strategies to Enable Locomotion after Spinal Cord Injury

Emanuele Formento

Spinal cord injury (SCI) is a major cause of paralysis with currently no effective treatment. Epidural electrical stimulation (EES) of the lumbar spinal cord has been shown to restore locomotion in animal models of SCI, but has not yet reached the same lev ...

EPFL2018

The role of uncertainty in dam failure frequency estimates: a conceptual case study

Anton Schleiss, José Pedro Gamito de Saldanha Calado Matos

The return period of combinations of events that are relevant to dam risk analysis is very high. It falls in a range of hundreds to millions of years, but remains hard to quantify with precision. Deterministic approaches to dam safety assessment typically ...

CRC Press/Balkema2018

Limits on Support Recovery with Probabilistic Models: An Information-Theoretic Framework

Volkan Cevher, Jonathan Mark Scarlett

The support recovery problem consists of deter- mining a sparse subset of a set of variables that is relevant in generating a set of observations, and arises in a diverse range of settings such as group testing, compressive sensing, and subset selection in ...

2015

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