UBC Okanagan Events

Irving K. Barber Faculty of Science

Name: Dissertation Defence: Interpretable Graph Distribution Representation Learning for Graph Optimization Problems
Start: 2025-06-13T10:00:00-07:00
End: 2025-06-13T14:00:00-07:00
Location: Arts Building (ART)

Events
Irving K. Barber Faculty of Science

May 2025

Mon 5

12:30 pm - 4:30 pm

Thesis Defence: Automating Superbubble 3D Segmentation in a Multiphase Interstellar Medium Using Computer Vision

Fri 9

9:30 am - 1:30 pm

Dissertation Defence: Regularities in Variational Analysis and Their Applications in Nonconvex Optimization

Mon 12

1:00 pm - 5:00 pm

Thesis Defence: Ecological Integrity Assessment for Monitoring Conservation Status and Restoration Success in Antelope Brush (Purshia tridentata) Ecosystems

Tue 20

9:00 am - 1:00 pm

Thesis Defence: Building an Atlas of Epitaxy in Metamorphic Rocks

Thu 29

9:00 am - 1:00 pm

Dissertation Defence: The Development of DNA-based Tools to Investigate Biomolecular Interactions Under Force

Jun 2025

Fri 13

10:00 am - 2:00 pm

Dissertation Defence: Interpretable Graph Distribution Representation Learning for Graph Optimization Problems

UBC Okanagan Campus

3333 University Way
Kelowna, BC Canada V1V 1V7
Tel 250 807 8000

We respectfully acknowledge the Syilx Okanagan Nation and their peoples, in whose traditional, ancestral, unceded territory UBC Okanagan is situated.

Irving K. Barber Faculty of Science

Thesis Defence: Automating Superbubble 3D Segmentation in a Multiphase Interstellar Medium Using Computer Vision

Dissertation Defence: Regularities in Variational Analysis and Their Applications in Nonconvex Optimization

Thesis Defence: Ecological Integrity Assessment for Monitoring Conservation Status and Restoration Success in Antelope Brush (Purshia tridentata) Ecosystems

Thesis Defence: Building an Atlas of Epitaxy in Metamorphic Rocks

Dissertation Defence: The Development of DNA-based Tools to Investigate Biomolecular Interactions Under Force

Dissertation Defence: Interpretable Graph Distribution Representation Learning for Graph Optimization Problems

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