no code implementations • ICLR 2019 • Swati Rallapalli, Liang Ma, Mudhakar Srivatsa, Ananthram Swami, Heesung Kwon, Graham Bent, Christopher Simpkin
Effectively capturing graph node sequences in the form of vector embeddings is critical to many applications.
2 code implementations • 30 Dec 2018 • Oytun Ulutan, Swati Rallapalli, Mudhakar Srivatsa, Carlos Torres, B. S. Manjunath
While observing complex events with multiple actors, humans do not assess each actor separately, but infer from the context.
no code implementations • 2 Aug 2018 • ShreeRanjani SrirangamSridharan, Oytun Ulutan, Shehzad Noor Taus Priyo, Swati Rallapalli, Mudhakar Srivatsa
However, the addition of a depth image can be further used to segment images that might otherwise have identical color information.
no code implementations • 27 Sep 2017 • Zongqing Lu, Swati Rallapalli, Kevin Chan, Thomas La Porta
In doing so Augur tackles several challenges: (i) how to overcome pro ling and measurement overhead; (ii) how to capture the variance in different mobile platforms with different processors, memory, and cache sizes; and (iii) how to account for the variance in the number, type and size of layers of the different CNN configurations.
no code implementations • 16 Oct 2016 • Archith J. Bency, Swati Rallapalli, Raghu K. Ganti, Mudhakar Srivatsa, B. S. Manjunath
Spatial Auto-Regression (SAR) is a common tool used to model such data, where the spatial contiguity matrix (W) encodes the spatial correlations.