Deep reinforcement learning (DRL) has proven extremely useful in a large...
Deep neural networks (DNNs) are increasingly being used as controllers i...
Recent developments in deep neural networks (DNNs) have led to their ado...
Deep neural networks (DNNs) are becoming a key component in diverse syst...
Deep neural networks (DNNs) are increasingly being deployed to perform
s...
Deep neural networks (DNNs) are the workhorses of deep learning, which
c...
Occlusion is a prevalent and easily realizable semantic perturbation to ...
Deep neural networks (DNNs) have become a crucial instrument in the soft...
Deep neural networks (DNNs) are a state-of-the-art technology, capable o...
In this short paper, we present our ongoing work on the veriFIRE project...
Reachability analysis is a promising technique to automatically prove or...
Deep Neural Networks (DNNs) are everywhere, frequently performing a fair...
With the rapid growth of machine learning, deep neural networks (DNNs) a...
Neural networks have become critical components of reactive systems in
v...
With the increasing application of deep learning in mission-critical sys...
With the increasing integration of neural networks as components in
miss...
Deep reinforcement learning (DRL) has achieved groundbreaking successes ...
Deep neural networks (DNNs) are increasingly being employed in
safety-cr...
Deep reinforcement learning (DRL) has become a dominant deep-learning
pa...
Inspired by sum-of-infeasibilities methods in convex optimization, we pr...
Deep reinforcement learning has proven remarkably useful in training age...
Deep neural networks (DNNs) have become the technology of choice for
rea...
Convolutional neural networks have gained vast popularity due to their
e...
Neural network models have become the leading solution for a large varie...
Deep neural networks (DNNs) have become increasingly popular in recent y...
Deep neural networks (DNNs) play an increasingly important role in vario...
Deep neural networks (DNNs) have gained significant popularity in recent...
Repairing legacy systems is a difficult and error-prone task: often, lim...
Deep learning has emerged as an effective approach for creating modern
s...
Neural networks (NN) learn complex non-convex functions, making them
des...
Deep neural networks (DNNs) are becoming prevalent, often outperforming
...
Inspired by recent successes with parallel optimization techniques for
s...
Deep neural networks are revolutionizing the way complex systems are
dev...
Deep neural networks are increasingly being used as controllers for
safe...
Deep neural network (DNN) verification is an emerging field, with divers...
Scenario-Based Programming is a methodology for modeling and constructin...
The increasing use of deep neural networks for safety-critical applicati...
Deep neural networks have become widely used, obtaining remarkable resul...
The ability to deploy neural networks in real-world, safety-critical sys...
Autonomous vehicles are highly complex systems, required to function rel...
Deep neural networks have emerged as a widely used and effective means f...