Heterogeneous Message Passing Neural Network for Semi-Supervised Learning
Task
Node attribute completion in knowledge graphs.
Description
In recent years, only a few graph representation learning (GRL) approaches have …
Eda Bayram
Available
Machine learning on time series, event detection, classification and prediction
This project is in collaboration with the Paul Scherrer Institute. The goal is to better understand the mechanical phenomena appearing …
Benjamin Ricaud
Available
Development of a high performance plasma-based actuator for active noise reduction
The development of novel noise reduction technologies is challenged by the growing environmental noise pollution concerns. Since conventional passive noise …
Stanislav Sergeev
Available
Development, assessment and optimization of an Active Nonlinear Electroacoustic Resonator
Acoustic metamaterials (AMMs) and metasurfaces (AMSs) are engineered structures aimed at achieving unprecedented acoustic properties not available in nature. They …
Xinxin Guo
Available
Room modes identification and characterization and its potential application
Room modes can significantly impair the quality of sound diffusion, in particular at low-frequencies and in small auditoria. These low-frequency …
Thach Pham Vu
Available
Implementation of a low-cost real-time reverberation algorithm
The LTS2-Acoustics is working on binaural audio synthesis for applications in hearing aid technologies. Our activities deal with the improvement …
Vincent Grimaldi
Available
VENOVA : an actively modified cylindrical cross-saxophone
After some research, modeling, computations, adjustments and a bit of luck, the team of engineers from Yamaha have developed a …
Hervé Lissek
Available
In-Situ Assessment of Active Electroacoustic Absorbers in Rooms at Low-Frequencies
Room modes can significantly impair the quality of sound diffusion, in particular at low-frequencies and in small auditoria. These low-frequency …
Thach Pham Vu
Available
Development of an active acoustic metasurface
Metamaterials are engineered materials with a subwavelength structure that enables extraordinary propagation and manipulation of waves. In acoustics, they can …
Maxime Volery
Available
Anomaly detection on large scale distributed sensors, combining signal processing and machine learning
This project may be done as a company internship for a master student, for the summer 2021 instead of a …
Benjamin Ricaud
Assigned
Deep Learning on Neuronal Morphologies
Project description at https://www.epfl.ch/research/domains/bluebrain/deep-learning-on-neuronal-morphologies-internship/.
Michaël Defferrard, Lida Kanari, Francesco Casalegno, Stanislav Schmidt
Assigned
Is my deep neural network good at memorizing?
Project Description
How much information have deep neural network weights memorized after training? One way of answering this question is …
Konstantinos Pitas
Assigned
How flat is my minimum?
Project Description
Predicting how a deep neural network will perform on new datapoints after training is important in real applications. …
Konstantinos Pitas
Assigned
Better Uncertainty Estimates for DNNs v2!
Project Description
Deriving uncertainty estimates for feedforward DNN predictions is critical in a number of tasks. For example you might …
Konstantinos Pitas
Assigned
Development of a microphone array to track mobile noise sources
Microphone arrays can be used to locate and track moving sound sources, thanks to advanced signal processing techniques. Such techniques …
Benjamin Ricaud, Hervé Lissek
Assigned
Geometric Deep Learning for Climate and Weather Modeling
Climate change is one of the grand challenges facing humanity in the 21st century.
Humankind can mainly act on two …
Michaël Defferrard, Gionata Ghiggi
Assigned
Multi-actuated panel for active sound absorption
The distributed mode loudspeaker (DML) technology is a flat panel loudspeaker from which sound is generated a set of electromechanical …
Hervé Lissek
Finished
Protein reconstruction from multiple images with Deep Learning
Single-particle cryo-electron microscopy (cryo-EM) is a Nobel-prized technology that aims to characterize the 3D structure of proteins at the atomic …
Michaël Defferrard, Laurène Donati
Finished
Learning on manifolds
In many applications, data lie on non-Euclidean manifolds.
Examples on the sphere include planetary data (such as temperature, wind, aerial …
Michaël Defferrard, Martino Milani
Finished
Data-driven research on graph neural networks
I am looking for motivated students that wish to work on the development of deep learning algorithms for graph data. …
Andreas Loukas
Finished
An empirical study of rotation equivariant neural networks
The goal of the project is to empirically study the difference in performance of Neural Networks that are either equivariant …
Michaël Defferrard
Finished
Assessment of Low-rank approximation techniques in sound field reconstruction
Room modes can significantly impair the quality of sound diffusion, in particular at low-frequencies and in small auditoria. In practice, …
Thach Pham Vu
Finished
Better uncertainty estimates for DNNs
DNNs are increasingly used in sensitive environments such as healthcare. In these sensitive environments a number of important questions arise. …
Konstantinos Pitas
Finished
Geometric Deep Learning for Fluid Dynamics
Use Machine Learning on graphs and manifolds to solve problems in computational fluid dynamics.
Michaël Defferrard
Finished
Music outside the head
In nature and most daily life situations, sounds of the world are naturally perceived as coming from outside the head. …
Vincent Grimaldi
Finished