Teaching

Fall 2023

Fall 2022

  • Leaning, Probabilities and Causality with Thomas Hueber, Eric Gaussier and Emilie Devijver (teaching resources in chamilo).
  • Advanced Machine Learning: Applications to Vision, Audio and Text with Karteek Alahari, Eric Gaussier, Didier Schwab and Georges Quénot (teaching resources in chamilo).

Fall 2021

  • Fundamentals of Probabilistic Data Mining with Thomas Hueber and Jean-Baptiste Durand (teaching resources in chamilo).
  • Machine Learning for Multimodal Data with Karteek Alahari, Eric Gaussier, Didier Schwab and Georges Quénot (teaching resources in chamilo).

Fall 2020

  • Fundamentals of Probabilistic Data Mining with Thomas Hueber (teaching resources in chamilo).
  • Machine Learning for Computer Vision and Audio Processing (ex Category Learning and Object Recognition) with Karteek Alahari (teaching resources in chamilo).

FALL 2019

  • Fundamentals of Probabilistic Data Mining (with Thomas Hueber and Fei Zheng). Course resources at chamilo (login required).
  • Category Learning and Object Recognition (with Karteek Alahari and Cordelia Schmidt). Webpage and resources.
  • Advanced Learning Models (with Julien Mairal). Webpage and resources.

Fall 2018

  • Fundamentals of Probabilistic Data Mining (with Jean-Baptiste Durand).

Talks

Invited Talks

Tutorials

  • Unsupervised Probabilistic Learning with Latent Variables, Machine Learning Summer School Africa 2023 (Jan’23). Slides.
  • Deep generative modeling of sequential data with dynamical variational autoencoders at IEEE ICASSP (May’21). Resources.
  • Audio-visual variational speech enhancement at Intelligent Sensing Summer School (Sep’20)
  • Probabilistic and deep regression for computer vision (ICIAP, Sep’19) [post]
  • Multimodal human behavior analysis in the wild (IAPR ICPR, Dec’16)
  • Learning from noisy and missing data (ACM Multimedia, Oct’16) [post]