Talks
Invited Talks and Tutorials
-
Molecule Representation Learning and Discovery: A Perspective from Topology, Geometry, and Textual Description
University of California, Berkeley, March 16th, 2023 -
ProteinDT: A Text-guided Protein Design Framework
NRC NLP seminar, March 10th, 2023 -
Molecule Representation Learning and Discovery: A Perspective from Topology, Geometry, and Textual Description
M2D2, Feb 14th, 2023 -
GraphCG: Unsupervised Discovery of Steerable Factors in Graphs
LOG, Meetup @ Mila, Dec 12th, 2022
[Slides] -
Self-Supervised Pretraining with 3D Molecular Geometry
Huawei, July 18th, 2022
[Slides] -
Pre-training Molecular Graph Representation with 3D Geometry – Rethinking Self-Supervised Learning on Structured Data
AI Times, March 31st, 2022
[Slides] -
Pre-training Molecular Graph Representation with 3D Geometry – Rethinking Self-Supervised Learning on Structured Data
Graph Reading Group, Mila, Feb 24th, 2022
[Slides] -
Pre-training Molecular Graph Representation with 3D Geometry – Rethinking Self-Supervised Learning on Structured Data
NLP Reading Group, University of Oxford, Feb 11th, 2022
[Slides] -
Molecular Representation Learning with Limited Data
Predoc-3 Presentation, Mila, Dec 9th, 2021
[Slides]
Group Meetings
- Foundation Model for Drug Discovery, Mila, Feb 2023
- Transformer and Self-Supervised Learning, Mila, Jan 2022
- Representation Learning Theory with Unlabeled Data, Mila, April 2021
- Contrastive (Self-Supervised) Leanring on Graphs and Some Thoughts, Mila, July 2020
- Multi-View Learning, Mila, June 2020
- Meta Learning, Mila, April 2020
- Drug Discovery: PriA-SSB Aldrich, UW2020, Apr 2019
- Negative Transfer in Deep Multi-task Learning, UW2020, Aug 2018
- Intro to Feature Representation in Virtual Screening, UW2020, Jan 2018