Publications

2016

1. Jesse A. Livezey, Alejandro F. Bujan, and Friedrich T. Sommer. On degeneracy control in overcomplete ICA. NIPS 2016 (submitted). http://arxiv.org/abs/1606.03474

2015

1. Evangelos Georganas, Aydın Buluc, Jarrod Chapman, Steven Hofmeyr, Chaitanya Aluru, Rob Egan, Leonid Oliker, Daniel Rokhsar, and Katherine Yelick. HiPMer: An extreme-scale de novo genome assembler. In International Conference for High Performance Computing, Networking, Storage and Analysis (SC’15), 2015.
2. Evangelos Georganas, Aydın Buluc, Jarrod Chapman,Leonid Oliker,Daniel Rokhsar, and Katherine Yelick. meraligner: A fully parallel sequence aligner. In Proceedings of the IPDPS, 2015.
3. Jarrod Chapman, Martin Mascher, Aydın Buluc, Kerrie Barry, Evangelos Georganas, Adam Session, Veronika Strnadova, Jerry Jenkins, Sunish Sehgal, Leonid Oliker, Jeremy Schmutz, Katherine Yelick, Uwe Scholz, Robbie Waugh, Jesse Poland, Gary Muehlbauer, Nils Stein, and Daniel Rokhsar. A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome. Genome Biology, 16(26), 2015.
4. Jiyan Yang, Oliver Rübel, Prabhat, Michael W. Mahoney, and Ben P. Bowen. Identifying Important Ions and Positions in Mass Spectrometry Imaging Data Using CUR Matrix Decompositions.Analytical Chemistry, 87(9), 4658-4666, 2015.
5. C. J. Hillar and F. T. Sommer: When can dictionary learning uniquely recover sparse data from subsamples? IEEE Transactions on Information Theory 61(11):6290-6297 (2015).
6. Regier, J., Miller, A., McAuliffe, J., Adams, R., Hoffman, M., Lang, D., Schlegel, D. & Prabhat. Celeste: Variational inference for a generative model of astronomical images. International Conference on Machine Learning, 2015.
7. Rippel, O., Snoek, J. & Adams, R.P. Spectral Representations for Convolutional Neural Networks. To Appear in Advances in Neural Information Processing Systems (NIPS), 2015.
8. Miller, A., Wu, A., Regier, J., McAuliffe, J., Prabhat, Schlegel, D., Lang, D. & Adams, R.P. A Gaussian Process Model of Quasar Spectral Energy Distributions. To Appear in Advances in Neural Information Processing Systems (NIPS), 2015.
9. Snoek, J., Rippel, O., Swersky, K., Kiros, R., Satish, N., Sundaram, N., Patwary, M.M.A., Prabhat & Adams, R.P.. Scalable Bayesian Optimization Using Deep Neural Networks. In Proceedings of the 32nd International Conference on Machine Learning (ICML), 2015.
10. Spectral Representations for Convolutional Neural Networks. Oren Rippel, Jasper Snoek and Ryan P. Adams. Neural Information Processing Systems, 2015.
11. “DB-CATS: Big Data Clustering at Trillion Scale”, Mostofa Patwary, Suren Byna, Nadathur Satish, Narayan Sundaram, Zarija Lukic, Vadim Roytershteyn, Michael Andrerson, Yushu Yao, Prabhat, Pradeep Dubey. In International Conference for High Performance Computing, Networking, Storage and Analysis (SC’15), 2015.
12. Regier, J., McAuliffe, J., Prabhat. A deep generative model for astronomical images of galaxies. NIPS 2015 workshop: Advances in approximate inference.

2014

1. Oren Rippel, Michael Gelbart and Ryan P. Adams. Learning Ordered Representations with Nested Dropout. Proceedings of the 31st International Conference on Machine Learning (ICML 2014). arXiv:1402.0915 [stat.ML].
2. Evangelos Georganas, Aydın Buluç, Jarrod Chapman, Leonid Oliker, Daniel Rokhsar, and Katherine Yelick. Parallel de bruijn graph construction and traversal for de novo genome assembly. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC'14), 2014.
3. Jeffrey Regier,  Brenton Partridge, Jon McAuliffe, Ryan Adams, Matt Hoefman, Dustin Lang, David Schlegel, Prabhat. Celeste: Scalable variational inference for a generative model of astronomical images. NIPS 2014 workshop: Advanced in variational inference.