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MoML 2023

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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Dominique Beaini.png

Dominique Beaini

Mila - Quebec AI Institute

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MIT

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Sergey Ovchinnikov

MIT

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Harvard University

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New York University

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MIT

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Mohammed AlQuraishi

Columbia University

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University of Pennsylvania

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Dominic Masters

Google DeepMind

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Mila

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Harvard University

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Djork-Arné Clevert

Pfizer

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University of Cambridge

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Queen's University

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Regina Barzilay

MIT

Conference Playlist

MoML 2024: Opening

Remarks

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Yoshua Bengio & Dominique Beaini

MoML 2023: Opening Remarks

Speakers: Yoshua Bengio & Dominique Beaini

OpenFold: Lessons Learned and Insights Gained From Rebuilding and Retraining AlphaFold2

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OpenFold: Lessons Learned and Insights Gained

From Rebuilding and Retraining AlphaFold2

Accelerating Cryptic

Pocket Discovery With

Deep Learning

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Accelerating Cryptic Pocket Discovery

With Deep Learning. Speaker: Greg Bowman

Molecular Machine

Learning at Scale:

Lessons from the OGB Large Scale Challenge

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Molecular Machine

Learning at Scale:

Lessons from the OGB Large Scale Challenge. Graphcore

On the Future of AI

for Drug Discovery

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Yoshua Bengio, Marinka Zitnik, Djork-Arné Clevert

On the Future of AI for Drug Discovery

Speaker: Yoshua Bengio, Marinka Zitnik, Djork-Arné Clevert

Watch full

playlist

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