Program

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)

  1. “The Riemannian Geometry of Deep Generative Models”,  Hang Shao, Abhishek Kumar, Tom Fletcher.
  2. “Elastic Approach For Handling Predictor Phase in Functional Regression Models”, Kyungmin Ahn, DerekTucker, Wei Wu, Anuj Srivastava.
  3. “Geodesic Discriminant Analysis for manifold-valued data”,  Maxime Louis, Benjamin Charlier, Stanley Durrleman.
  4. “A mixture model for aggregation of multiple pre-trained weak classifiers”,  Rudrasis Chakraborty, Chun-Hao Yang, Baba Vemuri.
  5. “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

  1. “Locally-Weighted Elastic Comparison of Planar Shapes”,  Justin Strait, Sebastian Kurtek, Steven MacEachern.
  2. “Covariance Pooling for Facial Expression Classification”,  Dinesh Acharya, Zhiwu Huang, Danda Pani Paudel, Luc Van Gool.
  3. “Image Segmentation by Deep Learning of Disjunctive Normal Shape Model Shape Representation”,  Mehran Javanmardi, Ricardo Bigolin Lanfredi, Mujdat Cetin, Tolga Tasdizen.
  4. “Predicting Dynamical Evolution of Human Activity from a Single Image”,  Suhas Lohit, Ankan Bansal, Nitesh Shroff, Jaishanker Pillai, Pavan Turaga, Rama Chellappa.
  5. “A unified view of coding methods based on the log-Euclidean and affine invariant Riemannian metric”,  Ioana Ilea, Lionel Bombrun, Salem Said, Yannick Berthoumieu.
  6. “Principal Curvature Guided Surface Geometry Aware Global Shape Representation”,  Somenath Das, Suchendra Bhandarkar.
  7. “SphereNet: Learning Spherical Representations for Classification of Omnidirectional Images”, Benjamin Coors, Alexandru Condurache, Andreas Geiger.
  8. “Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation”, Pietro Morerio, Jacopo Cavazza, Vittorio Murino
  9. “DEFRAG: Deep Euclidean Feature Representations through Adaptation on the Grassmann Manifold”, Breton Minnehan, Andreas Savakis.
  10. “Localizing Differentially Evolving Covariance Structures via Scan Statistics”, Ronak Mehta, Hyunwoo J. Kim, Shulei Wang, Sterling C. Johnson, Ming Yuan, Vikas Singh.