9:00am Welcome Remarks
9:05am Poster spotlights, 2 mins each
9:30am Keynote “Geometric deep learning on manifolds and graphs”, Michael Bronstein.
10:10am Coffee break and posters
10:30am Oral Presentations (20 mins each)
- “The Riemannian Geometry of Deep Generative Models”, Hang Shao, Abhishek Kumar, Tom Fletcher.
- “Elastic Approach For Handling Predictor Phase in Functional Regression Models”, Kyungmin Ahn, DerekTucker, Wei Wu, Anuj Srivastava.
- “Geodesic Discriminant Analysis for manifold-valued data”, Maxime Louis, Benjamin Charlier, Stanley Durrleman.
- “A mixture model for aggregation of multiple pre-trained weak classifiers”, Rudrasis Chakraborty, Chun-Hao Yang, Baba Vemuri.
- “Temporal Alignment Improves Feature Quality: an Experiment on Activity Recognition with Accelerometer Data”, Hongjun Choi, Qiao Wang, Meynard Toledo, Matthew Buman, Pavan Turaga, Anuj Srivastava.
12:10pm Lunch Break
2:00pm Keynote “The Geometry of the Loss Function for Deep Networks and its Role in Generalization”, Stefano Soatto.
2:40pm Keynote “Optimisation Geometry”, Jonathan Manton.
3:20pm Keynote “Probabilistic Geodesic Models for Dimensionality Reduction and Regression on Manifolds”, Tom Fletcher.
4:00pm Keynote “Machine Learning Approaches for Medical Image Registration”, Marc Niethammer.
4:40pm Poster Session
- “Locally-Weighted Elastic Comparison of Planar Shapes”, Justin Strait, Sebastian Kurtek, Steven MacEachern.
- “Covariance Pooling for Facial Expression Classification”, Dinesh Acharya, Zhiwu Huang, Danda Pani Paudel, Luc Van Gool.
- “Image Segmentation by Deep Learning of Disjunctive Normal Shape Model Shape Representation”, Mehran Javanmardi, Ricardo Bigolin Lanfredi, Mujdat Cetin, Tolga Tasdizen.
- “Predicting Dynamical Evolution of Human Activity from a Single Image”, Suhas Lohit, Ankan Bansal, Nitesh Shroff, Jaishanker Pillai, Pavan Turaga, Rama Chellappa.
- “A unified view of coding methods based on the log-Euclidean and affine invariant Riemannian metric”, Ioana Ilea, Lionel Bombrun, Salem Said, Yannick Berthoumieu.
- “Principal Curvature Guided Surface Geometry Aware Global Shape Representation”, Somenath Das, Suchendra Bhandarkar.
- “SphereNet: Learning Spherical Representations for Classification of Omnidirectional Images”, Benjamin Coors, Alexandru Condurache, Andreas Geiger.
- “Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation”, Pietro Morerio, Jacopo Cavazza, Vittorio Murino
- “DEFRAG: Deep Euclidean Feature Representations through Adaptation on the Grassmann Manifold”, Breton Minnehan, Andreas Savakis.
- “Localizing Differentially Evolving Covariance Structures via Scan Statistics”, Ronak Mehta, Hyunwoo J. Kim, Shulei Wang, Sterling C. Johnson, Ming Yuan, Vikas Singh.