Deep Learning and Medical Applications - IPAM

Deep Learning and Medical Applications

January 27 - 31, 2020

Schedule

All times in this Schedule are Pacific Time (PT)

Monday, January 27, 2020

Morning Session

08:00-08:55
Check-In/Light Breakfast (Hosted by IPAM)
08:55-09:00
Welcome & Opening Remarks: Dean Miguel García-Garibay (Dean of Physical Sciences, UCLA) and Dima Shlyakhtenko (Director, IPAM)
09:00-09:50
Jin Keun Seo (Yonsei University)
Deep Learning-Based Solvability of Underdetermined Inverse Problems in Medical Imaging
10:00-10:15
Break
10:15-11:05
Lars Ruthotto (Emory University)
A Machine Learning Framework for Optimal Transport of High-Dimensional Densities
11:15-11:30
Break
11:30-12:20
Michael Unser (École Polytechnique Fédérale de Lausanne (EPFL))
Splines and imaging: From compressed sensing to deep neural networks

Afternoon Session

12:30-14:30
Lunch (on your own)
14:30-15:20
Stanley Osher (University of California, Los Angeles (UCLA))
Trustworthy deep learning
15:30-16:30
Break
16:30-17:30
Jill Mesirov (University of California, San Diego (UCSD))
Can We Use Genomics to Better Understand and Treat Cancer?
17:30-19:00
Poster Session & Reception (Hosted by IPAM)

Tuesday, January 28, 2020

Morning Session

08:00-09:00
Check-In/Breakfast (Hosted by IPAM)
09:00-09:50
Ulugbek Kamilov (Washington University in St. Louis)
Computational Imaging: Reconciling Models and Learning
10:00-10:15
Break
10:15-11:05
Dosik Hwang (Yonsei University)
Deep Learning-based MR Image Reconstruction and Contrast Conversion.
11:15-11:30
Break
11:30-12:20
Georg Langs (Medizinische Universität Wien)
Deep learning for anomaly detection: expanding our marker vocabulary

Afternoon Session

12:30-13:45
Lunch (on your own)
13:45-14:35
Gitta Kutyniok (Ludwig-Maximilians-Universität München)
Deep Learning and Modeling: Taking the Best out of Both Worlds
14:45-15:00
Break
15:00-15:50
Jong Chul Ye (Korea Advanced Institute of Science and Technology (KAIST))
Geometric Understanding of Supervised and Unsupervised Deep Learning for Biomedical Image Reconstruction
16:30-17:30
Jill Mesirov (University of California, San Diego (UCSD))
Computational Genomic Approaches to the Understanding and Treatment of Cancer
17:30-19:00
Reception (Location: IPAM Lobby)

Wednesday, January 29, 2020

Morning Session

08:00-09:00
Check-In/Breakfast (Hosted by IPAM)
09:00-09:50
Jill Mesirov (University of California, San Diego (UCSD))
Molecular signatures drive the understanding and treatment of cancer
10:00-10:15
Break
10:15-11:05
Ivana Isgum (Amsterdam University Medical Center)
Deep learning for cardiovascular image analysis
11:15-11:30
Break
11:30-12:20
Jamie Haddock (University of California, Los Angeles (UCLA))
Scaling the Hierarchical Topic Modeling Mountain: Neural NMF and Iterative Projection Methods

Afternoon Session

12:30-14:30
Lunch (on your own)
14:30-15:20
Bao Wang (University of Utah)
Momentum in Stochastic Gradient Descent and Deep Neural Nets
15:30-16:00
Break
16:00-16:50
Pablo Suarez-Serrato (University of California, Santa Barbara (UCSB))
Quantifying the Topology of Coma

Thursday, January 30, 2020

Morning Session

08:00-09:00
Check-In/Breakfast (Hosted by IPAM)
09:00-09:50
Florian Knoll (New York University)
MR image acquisition and reconstruction in the era of deep learning
10:00-10:15
Break
10:15-11:05
Ender Konukoglu (ETH Zurich)
On Bayesian models with networks for reconstruction and detection
11:15-11:30
Break
11:30-12:20
Tom Vercauteren (King's College London)
Flexible machine learning approaches for computer-assisted surgery

Afternoon Session

12:30-14:00
Lunch (on your own)
14:00-14:50
Greg Zaharchuk (Stanford University)
AI-based Image Transformation and its Impact on Radiology
15:00-15:15
Break
15:15-16:05
Ben Glocker (Imperial College)
Causality matters in medical imaging
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