Talks and Tutorials
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Physics-Inspired Geometric Pretraining for Molecule Representation
Tutorial, AAAI, Vancouver, Canada, 20th Feb, 2024
[Link] [Website] -
AI for Molecule Discovery with Multi-Modal Knowledge
Ph.D. Defense, Mila-UdeM, 20th July, 2023
[Slides] [Paper] -
Molecule Representation Learning and Discovery: A Perspective from Topology, Geometry, and Textual Description
University of California, Berkeley, 16th March, 2023 -
ProteinDT: A Text-guided Protein Design Framework
NRC NLP seminar, 10th March, 2023 -
Molecule Representation Learning and Discovery: A Perspective from Topology, Geometry, and Textual Description
M2D2, 14th Feb, 2023 -
GraphCG: Unsupervised Discovery of Steerable Factors in Graphs
LOG, Meetup @ Mila, 12th Dec, 2022
[Slides] -
Self-Supervised Pretraining with 3D Molecular Geometry
Huawei, 18th July, 2022
[Slides] -
Pre-training Molecular Graph Representation with 3D Geometry – Rethinking Self-Supervised Learning on Structured Data
AI Times, 31st March, 2022
[Slides] -
Pre-training Molecular Graph Representation with 3D Geometry – Rethinking Self-Supervised Learning on Structured Data
Graph Reading Group, Mila, 24th Feb, 2022
[Slides] -
Pre-training Molecular Graph Representation with 3D Geometry – Rethinking Self-Supervised Learning on Structured Data
NLP Reading Group, University of Oxford, 11th Feb, 2022
[Slides] -
Molecular Representation Learning with Limited Data
Predoc-3 Presentation, Mila-UdeM, 9th Dec, 2021
[Slides]