Short-term precipitation forecasting using Lagrangian Convolutional Neural Networks
Background
The high-resolution short-range forecasting (0–6h ahead) of precipitation (nowcasting) is an essential component of severe weather and hydrological early …
Gionata Ghiggi, Daniele Grattarola
Available
Short-term precipitation forecasting over Switzerland using Conditional Generative Adversarial Networks.
Background
The high-resolution short-range forecasting (0–6h ahead) of precipitation (nowcasting) is an essential component of severe weather and hydrological early …
Gionata Ghiggi, Daniele Grattarola
Available
Exploring Implicit Neural Representations from a Signal Processing Perspective
Background.
Implicit neural representations (INRs) have recently emerged as a powerful way of representing signals using neural networks.
INRs are …
Daniele Grattarola
Available
Adaptive Neural Cellular Automata
Background:
Neural Cellular Automata (NCA) are a class of cellular automata that use neural networks as learnable transition rules.
By …
Daniele Grattarola
Available
Adaptive geometric neural networks
Background: Networks are powerful mathematical objects which are widely used to model systems composed of interacting constituents such as those …
Adám Gosztolai
Available
A Generalized Representation of Chemical Entities for Machine Learning Tasks
What's it about. Machine learning on big chemical data has recently produced intriguing results and was shown to be capable …
Daniel Probst
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
Traffic noise Radar: Tracking and estimation of individual vehicle noise emission
Traffic noise and its effects on health has become increasingly more relevant these days. The latest noise emission model, SonRoad18, …
Thach Pham Vu
Assigned
Granular synthesis applied to car sound design
Granular synthesis is an alternative to conventional sound synthesis (additive, substractive or frequency modulation, among others), not relying on manipulating …
Thach Pham Vu, Vincent Grimaldi
Assigned
Development of a plasma sound absorber
Plasma technology can be used for sound diffusion without resorting to a vibrating membrane and a cumbersome driver (as in …
Stanislav Sergeev
Assigned
Controlling the timbre of wind instruments with active impedance control
A wind instrument can generally be assimilated to a axisymmetric hollow duct, with varying (or constant) cross-section along the main …
Maxime Volery
Assigned
Graph Neural Networks applied to team sports
Project Description
Team sports rely on highly tactical and complex strategies often suggested by coaching staffs. For instance, basketball is …
Ali Hariri
Assigned
Machine learning for urban traffic classification
In Switzerland, more than 1 million people are concerned with traffic noise, which may have many adverse effects on health. …
Hervé Lissek
Finished
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
Finished
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
Finished
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
Finished
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
Finished
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
Finished
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
Finished
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
Finished
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
Finished
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
Finished
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
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
Finished
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
Finished