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 https://www.epfl.ch/research/domains/bluebrain/deep-learning-on-neuronal-morphologies-internship/.
Michaël Defferrard, Lida Kanari, Francesco Casalegno, Stanislav Schmidt
Finished