63 citations · 188 across the 14 of their papers we have counts for
4 papers · 1 filter
Automated flow for compressing convolution neural networks for efficient edge-computation with FPGA
Farhan Shafiq, Takato Yamada, Antonio T. Vilchez +1
Deep convolutional neural networks (CNN) based solutions are the current state- of-the-art for computer vision tasks. Due to the large size of these models, they are typically run…
Dynamic Boltzmann Machines for Second Order Moments and Generalized Gaussian Distributions
Rudy Raymond, Takayuki Osogami, Sakyasingha Dasgupta
Dynamic Boltzmann Machine (DyBM) has been shown highly efficient to predict time-series data. Gaussian DyBM is a DyBM that assumes the predicted data is generated by a Gaussian dis…
Transfer learning from synthetic to real images using variational autoencoders for robotic applications
Tadanobu Inoue, Subhajit Chaudhury, Giovanni De Magistris +1
Robotic learning in simulation environments provides a faster, more scalable, and safer training methodology than learning directly with physical robots. Also, synthesizing images…
Conditional generation of multi-modal data using constrained embedding space mapping
Subhajit Chaudhury, Sakyasingha Dasgupta, Asim Munawar +2
We present a conditional generative model that maps low-dimensional embeddings of multiple modalities of data to a common latent space hence extracting semantic relationships betwe…