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Title Description Supervisors Status
Implicit Neural Representations of Molecular Surfaces Coordinate-based neural networks, sometimes called Implicit Neural Representations (INRs), used for instance in NeRFs, learn to represent highly complex functions … Pierre Vandergheynst, Daniel Probst Available
Wavefunction collapse algorithm for de novo molecular design Summary. The wavefunction collapse algorithm is a conceptually simple generative algorithm inspired by wavefunction superposition [1]. The algorithm has been … Daniel Probst Available
Modeling translation elongation dynamics through Variational AutoEncoders Background Ribosome profiling [1] enabled in vivo monitoring of translation, allowing us to measure codon-specific ribosome dwell times. Recently, computational … Mohan Vamsi Nallapareddy, Francesco Craighero Available
Enhancing Protein Design Through Advanced Graph Neural Networks Background: Machine learning has seen increasing applications in natural sciences, particularly biology. The powerful contributions of machine learning to the … Pengkang Guo Available
Efficient Graph Neural Networks for Point Cloud Processing Project Summary: In this work we address the scalability issues of point cloud methods. We will aim to develop more … Ali Hariri Available
Development and characterization of an acoustic matched source Nonlinear or time-varying systems have established a new paradigm in wave engineering as they push the limits of conventional materials. … Stanislav Sergeev, Matthieu Malléjac, Romain Fleury 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
Geometric deep learning in dynamical systems Background Geometric deep learning has made substantial impact in the machine learning community by generalising convolution operations, previously defined on … Adám Gosztolai Assigned
Learning principles of robotic locomotion on insects Background Robotics and AI research has achieved significant feats in recent years so that current legged robots can perform a … Adám Gosztolai Assigned
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
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
Self-Supervised Learning for ribosome detection in microscopy images Background: In biomedical research, the detection, counting, and localization of ribosome spots from fluorescent imaging data is crucial for various … Mohan Vamsi Nallapareddy Finished
Manifold learning applications on graphs and videos Background: Representation learning of both structured and graph data is mostly performed in Euclidean space. Earlier studies have shed light … Ali Hariri Finished
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 Finished
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 Finished
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 Finished
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 Finished
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 Finished
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 Finished
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 Michaël Defferrard, Lida Kanari, Francesco Casalegno, Stanislav Schmidt Finished