Machine Learning for Life Sciences
15-17 nov. 2022 Montpellier (France)
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Programme
Mar. 15
Mer. 16
Jeu. 17
Mar. 15
Mer. 16
Jeu. 17
09:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
Welcome / coffee
13:00 - 13:50 (50min)
Welcome / coffee
Welcome / coffee
Introduction and practical information.
13:50 - 14:00 (10min)
Introduction and practical information.
Keynote
14:00 - 15:00 (1h)
Keynote
Speaker: Gabriel Peyré. Title: Optimal Transport and its Applications for Single Cell Genomics
Pause Café
15:00 - 15:30 (30min)
Pause Café
Keynote
15:30 - 16:30 (1h)
Keynote
Speaker: Bertrand Thirion. Title: Enhancing our understanding of brain function with machine learning on large-scale data repositories.
Keynote
16:30 - 17:30 (1h)
Keynote
Speaker: Stephen Becker. Title: Introduction to compressed sensing and matrix completion
Keynote
9:00 - 10:00 (1h)
Keynote
Speaker: Flora Jay. Title: Digging Historical Diversity Patterns out of Large-Scale Genomic Data using Exchangeable and Generative Neural Networks
Pause
10:00 - 10:30 (30min)
Pause
Keynote
10:30 - 11:30 (1h)
Keynote
Speaker: Julien Chiquet. Title: The Poisson-Lognormal Model as a Versatile Framework for the Joint Analysis of Species Abundances
Keynote
11:30 - 12:30 (1h)
Keynote
Speaker: Michael Blum. Title: Machine Learning applications in personalized medicine.
Déjeuner
12:30 - 14:00 (1h30)
Déjeuner
Keynote
14:00 - 15:00 (1h)
Keynote
Speaker: Emmanuel Faure. Title: MorphoDeep : a toolbox to curate fluorescence microscopy images
Pause
15:00 - 15:30 (30min)
Pause
Keynote
15:30 - 16:30 (1h)
Keynote
Speaker: Nathalie Vialaneix. Title: Multi-omics data integration methods: kernel and other machine learning approaches
Keynote
9:00 - 10:00 (1h)
Keynote
Speaker: Yun S. Song. Title: Improving Variant Effect Predictions using Language Models and Cross-Protein Transfer Learning
Pause
10:00 - 10:30 (30min)
Pause
Keynote
10:30 - 11:30 (1h)
Keynote
Speaker: Charles-Henri Lecellier. Title: Machine learning to probe novel regulatory elements in the human genome
Keynote
11:30 - 12:30 (1h)
Keynote
Speaker: Diego Marcos. Title: Evaluating plant trait descriptions crawled from the Web.
Déjeuner
12:30 - 14:00 (1h30)
Déjeuner
Keynote
14:00 - 15:00 (1h)
Keynote
Speaker: Sophie Donnet. Title: Modeling collections of networks by stochastic block models. Application in ecology and sociology.
Keynote
15:00 - 16:00 (1h)
Keynote
Speaker: Tim Landgraf. Title: BeesBook: Machine learning for the analysis of honeybee social behavior
Pause
16:00 - 16:30 (30min)
Pause
Keynote
16:30 - 17:30 (1h)
Keynote
Speaker: Daniele Silvestro. Title: Using artificial intelligence to predict future biodiversity trends and guide conservation efforts
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