Concept
Computational resource
Related publications (134)
Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation
Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power.Simultaneously, a critical pain point arises as several computer vision applications are deployed ...
EPFL2024The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry
While the introduction of practical deep learning has driven progress across scientific fields, recent research highlighted that the requirement of deep learning for ever-increasing computational resources and data has potential negative impacts on the sci ...
2023Expectation consistency for calibration of neural networks
Florent Gérard Krzakala, Lenka Zdeborová, Lucas Andry Clarte, Bruno Loureiro
Despite their incredible performance, it is well reported that deep neural networks tend to be overoptimistic about their prediction confidence. Finding effective and efficient calibration methods for neural networks is therefore an important endeavour tow ...
2023Confidence Matters: Applications to Semantic Segmentation
The successes of deep learning for semantic segmentation can in be, in part, attributed to its scale: a notion that encapsulates the largeness of these computational architectures and the labeled datasets they are trained on. These resource requirements hi ...
EPFL2023Evaluating the effect of sparse convolutions on point cloud compression
The use of point clouds as an imaging modality has been rapidly growing, motivating research on compression methods to enable efficient transmission and storage for many applications. While compression standards relying on conven- tional techniques such as ...
2023Democratizing Machine Learning
Nirupam Gupta, Alexandre David Olivier Maurer, Rafaël Benjamin Pinot
The increasing prevalence of personal devices motivates the design of algorithms that can leverage their computing power, together with the data they generate, in order to build privacy-preserving and effective machine learning models. However, traditional ...
IEEE2022