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6 x 3 minutes spotlights
Rémi Flamary · Yongxin Chen · Napat Rujeerapaiboon · Jonas Adler · John Lee · Lucas R Roberts

Sat Dec 09 10:00 AM -- 10:20 AM (PST) @
in Optimal Transport and Machine Learning »
  1. Nicolas Courty, Rémi Flamary and Mélanie Ducoffe. Learning Wasserstein Embeddings
  2. Yongxin Chen, Tryphon Georgiou and Allen Tannenbaum. Optimal transport for Gaussian mixture models
  3. Napat Rujeerapaiboon, Kilian Schindler, Daniel Kuhn and Wolfram Wiesemann. Size Matters: Cardinality-Constrained Clustering and Outlier Detection via Conic Optimization
  4. Jonas Adler, Axel Ringh, Ozan Öktem and Johan Karlsson. Learning to solve inverse problems using Wasserstein loss
  5. John Lee, Adam Charles, Nicholas Bertrand and Christopher Rozell. An Optimal Transport Tracking Regularizer
  6. Lucas Roberts, Leo Razoumov, Lin Su and Yuyang Wang. Gini-regularized Optimal Transport with an Application in Spatio-Temporal Forecasting

Author Information

Rémi Flamary (Université Côte d'Azur)
Yongxin Chen (Iowa State University)
Napat Rujeerapaiboon (EPFL)
Jonas Adler (KTH - Royal Institute of Technology)

I’m a Research Scientist at Elekta, pursuing a PhD in Applied Mathematics working under the supervision of Ozan Öktem. I do research in inverse problems and machine learning, especially focusing on the intersection between model-driven and data-driven methods. Organizing [DLIP2019](https://sites.google.com/view/dlip2019).

John Lee (Georgia Institute of Technology)
Lucas R Roberts (Virginia Tech)

```Research Scientist at Amazon since 2016 Phd in statistics from Virginia Tech SciPy developer/member ```

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