Related publications (24)

SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization

Olga Fink, Ismail Nejjar, Han Sun, Hao Dong

In real-world scenarios, achieving domain generalization (DG) presents significant challenges as models are required to generalize to unknown target distributions. Generalizing to unseen multi-modal distributions poses even greater difficulties due to the ...
2023

Transformer Models for Vision

Jean-Baptiste Francis Marie Juliette Cordonnier

The recent developments of deep learning cover a wide variety of tasks such as image classification, text translation, playing go, and folding proteins.All these successful methods depend on a gradient-based learning algorithm to train a model on massive a ...
EPFL2023

Keep Sensors in Check: Disentangling Country-Level Generalization Issues in Mobile Sensor-Based Models with Diversity Scores

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Machine learning models trained with passive sensor data from mobile devices can be used to perform various inferences pertaining to activity recognition, context awareness, and health and well-being. Prior work has improved inference performance through t ...
New York2023

4M: Massively Multimodal Masked Modeling

Shuqing Teresa Yeo, Amir Roshan Zamir, Oguzhan Fatih Kar, Roman Christian Bachmann, David Mizrahi

Current machine learning models for vision are often highly specialized and limited to a single modality and task. In contrast, recent large language models exhibit a wide range of capabilities, hinting at a possibility for similarly versatile models in co ...
Neural Information Processing Systems (Nips)2023

Temporal analysis of multimodal data to predict collaborative learning outcomes

Kshitij Sharma, Jennifer Kaitlyn Olsen

The analysis of multiple data streams is a long-standing practice within educational research. Both multimodal data analysis and temporal analysis have been applied successfully, but in the area of collaborative learning, very few studies have investigated ...
WILEY2020

Modes and Existences in Citizen Science: Thoughts from Earthquake Country

In the Bay Area of San Francisco, the earthquake contours are not easy to define: seismology is still a relatively recent science, and controversies around methods to evaluate the earthquake risk are constant. In this context, the invitation to think about ...
2019

Context-based Quality of Experience in Immersive Multimedia

Anne-Flore Nicole Marie Perrin

Since 1895, when the Lumière brothers came out with the projected cinematograph, motion pictures and more generally multimedia contents have considerably improved and are still experiencing a very dynamic development. Advances involved improving various mo ...
EPFL2019

Behavioral, Modeling, and Electrophysiological Evidence for Supramodality in Human Metacognition

Olaf Blanke, Nathan Quentin Faivre

Human metacognition, or the capacity to introspect on one's own mental states, has been mostly characterized through confidence reports in visual tasks. A pressing question is to what extent results from visual studies generalize to other domains. Answerin ...
2018

Microwave Imaging of Brain Stroke

Mina Bjelogrlic

Brain stroke is an age-related illness which has become a major issue in our ageing societies. Early diagnosis and treatment are of high importance for the full recovery of the patient, as reminded in Anglo-Saxon countries by the abbreviation FAST (Face, A ...
EPFL2018

Heterogeneous Face Recognition using Inter-Session Variability Modelling

Sébastien Marcel, Tiago De Freitas Pereira

The task of Heterogeneous Face Recognition consists in to match face images that were sensed in different modalities, such as sketches to photographs, thermal images to photographs or near infrared to photographs. In this preliminary work we introduce a no ...
IEEE2016

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.