no code implementations • 26 Sep 2023 • Ankur Mali, Alexander Ororbia, Daniel Kifer, Lee Giles
In this work, we extend the theoretical foundation for the $2^{nd}$-order recurrent network ($2^{nd}$ RNN) and prove there exists a class of a $2^{nd}$ RNN that is Turing-complete with bounded time.
no code implementations • 27 Jan 2022 • Ankur Mali, Alexander Ororbia, Daniel Kifer, Lee Giles
In light of this, we propose a system that learns to improve the encoding performance by enhancing its internal neural representations on both the encoder and decoder ends, an approach we call Neural JPEG.
no code implementations • 27 Jan 2022 • Ankur Mali, Alexander Ororbia, Daniel Kifer, Lee Giles
Recent advances in deep learning have resulted in image compression algorithms that outperform JPEG and JPEG 2000 on the standard Kodak benchmark.
1 code implementation • NAACL (sdp) 2021 • Athar Sefid, Jian Wu, Prasenjit Mitra, Lee Giles
Presentation slides describing the content of scientific and technical papers are an efficient and effective way to present that work.
1 code implementation • 19 Apr 2021 • Shivansh Rao, Vikas Kumar, Daniel Kifer, Lee Giles, Ankur Mali
A common approach has been to use standard convolutional networks to predict the corners and boundaries, followed by post-processing to generate the 3D layout.