Graph Convolutional Networks (GCNs) are pivotal in extracting latent
inf...
Two-party computation (2PC) is promising to enable privacy-preserving de...
Optical flow is an indispensable building block for various important
co...
Manual analysis of XRD data is usually laborious and time consuming. The...
The proliferation of deep learning (DL) has led to the emergence of priv...
In recent years, graph representation learning has gained significant
po...
The rapid growth and deployment of deep learning (DL) has witnessed emer...
The increasing size of input graphs for graph neural networks (GNNs)
hig...
As real-world graphs expand in size, larger GNN models with billions of
...
Transformers are considered one of the most important deep learning mode...
Graph Neural Networks (GNNs) have drawn tremendous attention due to thei...
With the increasing popularity of robotics in industrial control and
aut...
Tensor Cores have been an important unit to accelerate Fused Matrix
Mult...
Binary neural networks (BNNs) show promising utilization in cost and
pow...
Graph Convolutional Networks (GCNs) have drawn tremendous attention in t...
Graph Convolutional Networks (GCNs) have emerged as the state-of-the-art...
Graph Neural Networks (GNNs) have emerged as the state-of-the-art (SOTA)...
Molecular similarity search has been widely used in drug discovery to
id...
Being able to learn from complex data with phase information is imperati...
As supercomputers continue to grow to exascale, the amount of data that ...
Over the years, accelerating neural networks with quantization has been
...
Binarized neural networks, or BNNs, show great promise in edge-side
appl...
Comparison Lift is an experimentation-as-a-service (EaaS) application fo...
Recurrent neural networks (RNNs) have been widely adopted in temporal
se...
The recent development of deep learning has mostly been focusing on Eucl...
Firms implementing digital advertising campaigns face a complex problem ...
The implementation of Molecular Dynamics (MD) on FPGAs has received
subs...
Deep Neural Networks (DNNs) have revolutionized numerous applications, b...