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2020 – today
- 2022
[c9]Evgenya Pergament, Pulkit Tandon, Kedar Tatwawadi, Oren Rippel, Lubomir D. Bourdev, Bruno A. Olshausen, Tsachy Weissman, Sachin Katti, Alexander G. Anderson:
An Interactive Annotation Tool for Perceptual Video Compression. QoMEX 2022: 1-6- 2021
- [c8]Oren Rippel, Alexander G. Anderson, Kedar Tatwawadi, Sanjay Nair, Craig Lytle, Lubomir D. Bourdev:
ELF-VC: Efficient Learned Flexible-Rate Video Coding. ICCV 2021: 14459-14468 - [i7]Oren Rippel, Alexander G. Anderson, Kedar Tatwawadi, Sanjay Nair, Craig Lytle, Lubomir D. Bourdev:
ELF-VC: Efficient Learned Flexible-Rate Video Coding. CoRR abs/2104.14335 (2021)
2010 – 2019
- 2019
- [c7]Oren Rippel, Sanjay Nair, Carissa Lew, Steve Branson, Alexander G. Anderson, Lubomir D. Bourdev:
Learned Video Compression. ICCV 2019: 3453-3462 - 2018
- [i6]Oren Rippel, Sanjay Nair, Carissa Lew, Steve Branson, Alexander G. Anderson, Lubomir D. Bourdev:
Learned Video Compression. CoRR abs/1811.06981 (2018) - 2017
- [c6]Oren Rippel, Lubomir D. Bourdev:
Real-Time Adaptive Image Compression. ICML 2017: 2922-2930 - [i5]Oren Rippel, Lubomir D. Bourdev:
Real-Time Adaptive Image Compression. CoRR abs/1705.05823 (2017) - 2016
- [c5]Oren Rippel, Manohar Paluri, Piotr Dollár, Lubomir D. Bourdev:
Metric Learning with Adaptive Density Discrimination. ICLR (Poster) 2016 - 2015
- [c4]Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Md. Mostofa Ali Patwary, Prabhat, Ryan P. Adams:
Scalable Bayesian Optimization Using Deep Neural Networks. ICML 2015: 2171-2180 - [c3]Oren Rippel, Jasper Snoek, Ryan P. Adams:
Spectral Representations for Convolutional Neural Networks. NIPS 2015: 2449-2457 - [i4]Oren Rippel, Jasper Snoek, Ryan P. Adams:
Spectral Representations for Convolutional Neural Networks. CoRR abs/1506.03767 (2015) - 2014
- [c2]David Duvenaud, Oren Rippel, Ryan P. Adams, Zoubin Ghahramani:
Avoiding pathologies in very deep networks. AISTATS 2014: 202-210 - [c1]Oren Rippel, Michael A. Gelbart, Ryan P. Adams:
Learning Ordered Representations with Nested Dropout. ICML 2014: 1746-1754 - [i3]Oren Rippel, Michael A. Gelbart, Ryan P. Adams:
Learning Ordered Representations with Nested Dropout. CoRR abs/1402.0915 (2014) - [i2]David Duvenaud, Oren Rippel, Ryan P. Adams, Zoubin Ghahramani:
Avoiding pathologies in very deep networks. CoRR abs/1402.5836 (2014) - 2013
- [i1]Oren Rippel, Ryan Prescott Adams:
High-Dimensional Probability Estimation with Deep Density Models. CoRR abs/1302.5125 (2013)
Coauthor Index
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