Collective operations are used in MPI programs to express common communication patterns, collective computations, or synchronization. In many collectives, such as MPI Allreduce, the intra-node…
With the recent advancements in AI, Intelligent Virtual Assistants (IVA) have become a ubiquitous part of every home. Going forward, we are witnessing a confluence…
Uncertainty estimation in deep neural networks is essential for designing reliable and robust AI systems. Applications such as video surveillance for identifying suspicious activities are…
Network pruning has emerged as a powerful technique for reducing the size of deep neural networks. Pruning uncovers high-performance subnetworks by taking a trained dense…
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a minimally invasive imaging technique which can be used for characterizing tumor biology and tumor response to radiotherapy.…
Real-time functional magnetic resonance imaging (rtfMRI) is an emerging approach for studying the functioning of the human brain. Computational challenges combined with high data velocity…
High-throughput DNA sequencing is the mainstay of modern genomics research. A common operation used in bioinformatic analysis for many applications of high-throughput sequencing is the…
We present a learning-based approach to computing solutions for certain NP-hard problems. Our approach combines deep learning techniques with useful algorithmic elements from classic heuristics.…
Deep neural networks (DNNs) are computationally/memory-intensive and vulnerable to adversarial attacks, making them prohibitive in some real-world applications. By converting dense models into sparse ones,…
