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Swiss Ai Research Overview Platform

28 Research Topics
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71 Application Fields
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34 Institutions
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UniBE
NLP
CV
ML
Visual Question Answering and Visual Turing Tests for Medical Imaging
 
EAWAG
ML
Universal Aspects in the Landscape and Dynamics of Deep Neural Networks
 
CSEM
ML
CV
Ultra-Low Power Visual Perception Systems
 
UNIGE
MAS
DS-KRR-S
TRACES
 
UNIGE
CV
ML
The 100µPET project: Pioneering ultra-high resolution molecular imaging
 
ETHZ
ML
Robotics
HMI
Robot Intelligence for the Real World
 
ETHZ
NLP
Representation Learning for Arbitrarily Long Richly Formatted Multimedia Documents
 
UNIBAS
ML
Quantum synchronization and quantum phase transitions in arrays of nano- and optomechanical systems
 
BFH
ML
Probabilistic Intraday Forecasting of Photovoltaic Power generation for the Swiss Plateau
 
ZHAW
ML
Gov-ELSI
Predictive chance modelling: Exploration of a new approach to professional decision-making in child protection
 
ETHZ
ML
PHENOFLOW: A multifaceted workflow of high-throughput field phenotyping for improved prediction of wheat performance in future climate scenarios based on assessment of dynamic changes of phenology
 
UNIGE
NLP
NLU4EHR: Natural Language Understanding for Electronic Health Records Analytics
 
USI
ML
ML2 - Multilevel and Domain Decomposition Methods for Machine Learning
 
FHNW
ML
Mitigating of Macro- and Micro-Plastics in Agriculture Soils using Hyperspectral Imaging (MIRACLE)
 
CHUV
CV
Medical image quality: Model observers of radiologists performing a search task and AI algorithms that include the anatomical texture in low-contrast CT diagnostics
 
UNINE
ML
Measuring, Understanding, and Predicting Mutual Fund Performance Worldwide
 
EPFL
ML
Learning and Inference via Information Measures
 
ML
Interpretable artificial intelligence for computational biology: extracting new insights from single-cell proteomic data.
 
UniBE
ML
Improving Interpretability. Philosophy of Science Perspectives on Machine Learning
 
UniBE
CV
ML
Image data validation for AI systems
 
USI
ML
HORD GNN: Higher-Order Relations and Dynamics in Graph Neural Networks
 
EPFL
ML
Graph Neural Networks for Explainable Artificial Intelligence
 
EPFL
ML
PSO
DOPE - Deep Optimization
 
EPFL
ML
NLP
Distributed Training of Transformers - Scalable, Private, Robust and Personalized
 
UNIGE
CV
ML
Digital Phenotyping of Autism Spectrum Disorders in Children
 
EPFL
ML
Data-driven approximation of haemodynamics by combined reduced order modeling and deep neural networks
 
ETHZ
ML
Advanced Learning Methods On Dedicated nano-Devices (ALMOND)
 
UniBE
CV
ML
A Learning Approach to Image Restoration and Motion Estimation without Ground Truth Data
1
Achim Walter
Andrea Dunbar
Angela Meyer
  Cesare Alippi
Christoph Bruder
  Prof.Claus Beisbart
  David Lätsch
  Prof.Douglas Teodoro
  Prof.Florian Weigert
François Bochud
  Dr.Giuseppe Iacobucci
Hy Dao
Marco Baity Jesi
Maria Rodriguez Martinez
Marie Schaer
Martin Jaggi
Mathieu Luisier
Michael C. Gastpar
  Moritz Geilinger
  Prof.Mrinmaya Sachan
  Pablo Márquez Neila
  Paolo Favaro
  Prof.Petar Nikolov Mandaliev
  Prof.Pierre Vandergheynst
Pierre-François Rüedi
  Prof.Raphael Sznitman
Rolf Krause
  Prof.Simone Deparis
Tobias Delbruck
  Prof.Volkan Cevher
1