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Hello, welcome to my github repository !

Graduated from an MSc. Engineer degree (French « Grandes Écoles ») and a Research Master (MVA), I am passionated for mathematics and its applications, especially in artificial intelligence (deep learning, reinforcement learning, machine perception, vision, sound) and random modelling (computational statistics, state-space models, stochastic calculus).

I am currently a Ph.D. student at Télécom Paris and Valeo.ai and my research focuses on several problems related to distribution learning, uncertainty estimation and domain adaptation for complex tasks, especially with audio data.

Feel free to discover my favorites personnal or group projects in my repositories.

Languages :

Python R C Shell Script

ML/DL Frameworks :

PyTorch TensorFlow Pandas Numpy SciPy OpenCV

VictorLetzelter's Projects

algorithmic_trading icon algorithmic_trading

This repository contains an algorithmic trading project whose aim is to detect automatically divergences between a given asset, an a given momentum indicator. The algorithm is still to improve, and its efficiency and robustness to be tested (See the Notebook file in the Trading_project folder).

brownian_motion icon brownian_motion

This project has been realised in cooperation with two students : Hugo BESSON and Adrien CORTES. We tried to understand the analogy between the Brownian Motion used in physics, and the geometric Brownian used in financial mathematics. For those who are interested in the field, we provide you with our technical report.

code-rmcl icon code-rmcl

Code for associated with the NeurIPS23 publication 'Resilient Multiple Choice Learning: A learned scoring scheme with application to audio scene analysis'.

idinvert_pytorch icon idinvert_pytorch

[ECCV 2020] In-Domain GAN Inversion for Real Image Editing (PyTorch code)

multimodal-future-prediction icon multimodal-future-prediction

The official repository for the CVPR 2019 paper "Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction"

pattern_detection icon pattern_detection

This project consists on a technical study on the Stellarator TJ-II, an experimental device allowing to carry out experiments of turbulent plasmas at high temperature confined by magnetic fields. More precisely, an algorithm for the automatic detection of patterns in the time series of the electrostatic potential measured in the plasma was constructed. For this purpose, a probabilistic model was designed to simulate additional data to those provided and to train a neural network. These patterns correspond to specific events within the reactor: the "Zonal Flows"; this detection is relevant insofar as the understanding and detection of these hazards allows the improvement of the magnetic confinement of the plasma.

praudio icon praudio

Audio preprocessing framework for Deep Learning audio applications

pyemd icon pyemd

Fast EMD for Python: a wrapper for Pele and Werman's C++ implementation of the Earth Mover's Distance metric

pytorch icon pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorch-project-template-1 icon pytorch-project-template-1

A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.

seld-dcase2019 icon seld-dcase2019

Benchmark for sound event localization task of DCASE 2019 challenge

seld-dcase2022 icon seld-dcase2022

Baseline method for sound event localization task of DCASE 2022 challenge

seld-net icon seld-net

Sound event localization, detection, and tracking of multiple overlapping and moving sources in 2D spherical space using convolutional recurrent neural network

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