Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper.
Query: Toward Scalable Verification for Safety-Critical Deep Networks
An abstraction-refinement approach to verification of artificial neural networks
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability
Proteus: Exploiting Numerical Precision Variability in Deep Neural Networks
A Provably Efficient Algorithm for Training Deep Networks
Formal Specification for Deep Neural Networks
A Unified View of Piecewise Linear Neural Network Verification
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients
Survey of scaling platforms for Deep Neural Networks
Improving the Robustness of Deep Neural Networks via Stability Training
Imposing Hard Constraints on Deep Networks: Promises and Limitations
Towards Evaluating the Robustness of Neural Networks
Fast Homomorphic Evaluation of Deep Discretized Neural Networks.
Towards Deep Neural Network Architectures Robust to Adversarial Examples
An Explainable Adversarial Robustness Metric for Deep Learning Neural Networks
Measuring Invariances in Deep Networks
Testing Deep Neural Networks
Output Reachable Set Estimation and Verification for Multilayer Neural Networks
DeepSecure: Scalable Provably-Secure Deep Learning
Towards Safe Deep Learning: Unsupervised Defense Against Generic Adversarial Attacks
Graphene-based Recyclable Photo-Absorbers for High-Efficiency Seawater Desalination.
AN EMPIRICAL COMPARISON OF THE USABILITY OF BPMN AND UML ACTIVITY DIAGRAMS FOR BUSINESS USERS
Analysis of high-performance floating-point arithmetic on FPGAs
Defining Domain Language of Graphical User Interfaces
Effective Background Model-Based RGB-D Dense Visual Odometry in a Dynamic Environment