Concept
Fallacy
Related publications (14)
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The success of the Neural Radiance Fields (NeRF) in novel view synthesis has inspired researchers to propose neural implicit scene reconstruction. However, most existing neural implicit reconstruction methods optimize perscene parameters and therefore lack ...
2024The inductive bias of deep learning: Connecting weights and functions
Years of a fierce competition have naturally selected the fittest deep learning algorithms. Yet, although these models work well in practice, we still lack a proper characterization of why they do so. This poses serious questions about the robustness, trus ...
EPFL2023The challenges of quasi-static and fatigue experiments of structural adhesives
Anastasios Vassilopoulos, Valentin Perruchoud
This paper presents the results of an experimental campaign designed specifically to investigate unexpected and unwanted failures observed during the quasi-static and fatigue tensile loading of structural adhesives. Simple finite element models were also d ...
ELSEVIER SCI LTD2022Scaling Language Features for Program Verification
Formal verification of real-world software systems remains challenging for a number of reasons, including lack of automation, friction in specifying properties, and limited support for the diverse programming paradigms used in industry. In this thesis we m ...
EPFL2022Person Retrieval in Surveillance Videos Via Deep Attribute Mining and Reasoning
Zhen Wei, Zhiye Wang, Peixia Li
Person retrieval largely relies on the appearance features of pedestrians. This task is rather more difficult in surveillance videos due to the limitations of extracting robust appearance features brought by the cross-view and cross-camera data with lower ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021Multitask Learning Over Graphs: An Approach for Distributed, Streaming Machine Learning
Ali H. Sayed, Jie Chen, Stefan Vlaski, Roula Nassif
The problem of simultaneously learning several related tasks has received considerable attention in several domains, especially in machine learning, with the so-called multitask learning (MTL) problem, or learning to learn problem [1], [2]. MTL is an appro ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020Reverse-Engineering Satire, or "Paper on Computational Humor Accepted despite Making Serious Advances"
Humor is an essential human trait. Efforts to understand humor have called out links between humor and the foundations of cognition, as well as the importance of humor in social engagement. As such, it is a promising and important subject of study, with re ...
ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2019Experimental warming differentially affects microbial structure and activity in two contrasted moisture sites in a Sphagnum-dominated peatland
Alexandre Buttler, Luca Bragazza, Vincent Eric Jules Jassey
Several studies on the impact of climate warming have indicated that peat decomposition/mineralization will be enhanced. Most of these studies deal with the impact of experimental warming during summer when prevalent abiotic conditions are favorable to dec ...
Elsevier2015Annotating the meaning of discourse connectives by looking at their translation: The translation-spotting technique
The various meanings of discourse connectives like while and however are difficult to identify and annotate, even for trained human annotators. This problem is all the more important that connectives are salient textual markers of cohesion and need to be c ...
2013Transformation of governance in the water sector: How to measure legitimate, efficient and effective performance?
Matthias Finger, Eva Lieberherr, Andreas Klinke
In the context of liberalization in the public utility sectors, performance criteria have mainly focused on efficiency and effectiveness. However, the realization that restructuring based on the latter criteria has not been consistently successful in the w ...
2010