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MoML 2024

Molecular Machine Learning Conference

Our Mission

This conference brings together students, experts, and leaders across

areas with the goal of advancing how machine learning methods can

address key scientific goals related to molecular modeling, molecular interactions, and  therapeutic design. The conference provides an open

and lively place to discuss, learn, and innovate, for students and

experts alike. 

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Meet the


Speakers

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Intrepid Labs

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Max Jaderberg.png
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Isomorphic Labs

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Valence Labs

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Conference Playlist

MoML 2024: Opening

Remarks

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MoML 2024: Opening Remarks

Speakers: Dominique Beaini & Jonathan Hsu

Geometric Deep Learning

for Protein Understanding

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Geometric Deep Learning for Protein Understanding

Speaker: Jian Tang

Polaris: Industry-Led Initiative to Critically

Assess ML for Real-World

Drug Discovery.

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Polaris: Industry-Led Initiative

to Critically Assess ML for Real-World Drug Discovery. Speaker: Cas Wognum

Efficiently Exploring Combinatorial

Perturbations From High Dimensional Observation

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Efficiently Exploring Combinatorial Perturbations

From High Dimensional Observation. Speaker: Jason Hartford

Leveraging Molecular ML 

+ Property Prediction in Drug Design.

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Leveraging Molecular ML

+ Property Prediction in Drug Design. Speaker: Raquel Rodríguez-Pérez

Watch full

playlist

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