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A theorem proving approach for automatically synthesizing visualizations of flow cytometry data.

, , , , , , , , and . BMC Bioinform., 18 (8): 245:1-245:11 (2017)

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On the Susceptibility of Deep Neural Networks to Natural Perturbations., , , , , and . AISafety@IJCAI, volume 2419 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)Automated Synthesis of Memristor Crossbars Using Deep Neural Networks., , , , , , and . FICTA (2), volume 1177 of Advances in Intelligent Systems and Computing, page 345-357. Springer, (2020)Attribution-driven Causal Analysis for Detection of Adversarial Examples., , , , , , , and . CoRR, (2019)Attacking NIST biometric image software using nonlinear optimization., , , , , and . Pattern Recognit. Lett., (2020)Attribution-Based Confidence Metric For Deep Neural Networks., , , , , , , and . NeurIPS, page 11826-11837. (2019)Predicting Heart Rate Variations of Deepfake Videos using Neural ODE., , , , , , and . ICCV Workshops, page 1721-1729. IEEE, (2019)In-Memory Execution of Compute Kernels Using Flow-Based Memristive Crossbar Computing., , , , and . ICRC, page 1-6. IEEE, (2017)Adversarial attacks on computer vision algorithms using natural perturbations., , , , , , and . IC3, page 1-6. IEEE Computer Society, (2017)SATYA : Defending Against Adversarial Attacks Using Statistical Hypothesis Testing., , , and . FPS, volume 10723 of Lecture Notes in Computer Science, page 277-292. Springer, (2017)A compact 8-bit adder design using in-memory memristive computing: Towards solving the Feynman Grand Prize challenge., , and . NANOARCH, page 67-72. IEEE, (2017)