受强制性开放获取政策约束的文章 - Susmit Jha了解详情
无法在其他位置公开访问的文章：8 篇
Toward an internet of battlefield things: A resilience perspective
T Abdelzaher, N Ayanian, T Basar, S Diggavi, J Diesner, D Ganesan, ...
Computer 51 (11), 24-36, 2018
强制性开放获取政策： US Department of Defense
Predicting out-of-distribution performance of deep neural networks using model conformance
R Kaur, S Jha, A Roy, O Sokolsky, I Lee
2023 IEEE International Conference on Assured Autonomy (ICAA), 19-28, 2023
强制性开放获取政策： US Department of Defense
Trinity ai co-designer for hierarchical oracle-guided design of cyber-physical systems
A Cobb, A Roy, D Elenius, S Jha
2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION), 42-44, 2022
强制性开放获取政策： US Department of Defense
Challenges and Opportunities in Neuro-Symbolic Composition of Foundation Models
S Jha, A Roy, A Cobb, A Berenbeim, ND Bastian
MILCOM 2023-2023 IEEE Military Communications Conference (MILCOM), 156-161, 2023
强制性开放获取政策： US Department of Defense
Principled OOD Detection via Multiple Testing
A Magesh, VV Veeravalli, A Roy, S Jha
2023 IEEE International Symposium on Information Theory (ISIT), 1026-1031, 2023
强制性开放获取政策： US National Science Foundation, US Department of Defense
On detection of out of distribution inputs in deep neural networks
S Jha, A Roy
2021 IEEE Third International Conference on Cognitive Machine Intelligence …, 2021
强制性开放获取政策： US National Science Foundation, US Department of Defense
Exploring The Predictive Capabilities of AlphaFold Using Adversarial Protein Sequences
IR Alkhouri, S Jha, A Beckus, G Atia, S Jha, R Ewetz, A Velasquez
IEEE Transactions on Artificial Intelligence, 2024
强制性开放获取政策： US National Science Foundation
Lightning Talk: Trinity-Assured Neuro-symbolic Model Inspired by Hierarchical Predictive Coding
S Jha
2023 60th ACM/IEEE Design Automation Conference (DAC), 1-2, 2023
强制性开放获取政策： US Department of Defense
可在其他位置公开访问的文章：47 篇
Output range analysis for deep feedforward neural networks
S Dutta, S Jha, S Sankaranarayanan, A Tiwari
NASA Formal Methods Symposium, 121-138, 2018
强制性开放获取政策： US National Science Foundation
A theory of formal synthesis via inductive learning
S Jha, SA Seshia
Acta Informatica 54, 693-726, 2017
强制性开放获取政策： US National Science Foundation, US Department of Defense
Trojdrl: evaluation of backdoor attacks on deep reinforcement learning
P Kiourti, K Wardega, S Jha, W Li
2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020
强制性开放获取政策： US National Science Foundation, US Department of Defense
The ELFIN mission
V Angelopoulos, E Tsai, L Bingley, C Shaffer, DL Turner, A Runov, W Li, ...
Space science reviews 216, 1-45, 2020
强制性开放获取政策： US National Science Foundation, US Department of Defense, US National …
Learning task specifications from demonstrations
M Vazquez-Chanlatte, S Jha, A Tiwari, MK Ho, S Seshia
Advances in neural information processing systems 31, 2018
强制性开放获取政策： US National Science Foundation, US Department of Defense
Learning and verification of feedback control systems using feedforward neural networks
S Dutta, S Jha, S Sankaranarayanan, A Tiwari
IFAC-PapersOnLine 51 (16), 151-156, 2018
强制性开放获取政策： US National Science Foundation
Learning certified control using contraction metric
D Sun, S Jha, C Fan
Conference on Robot Learning, 1519-1539, 2021
强制性开放获取政策： US National Science Foundation, US Department of Defense
Attribution-based confidence metric for deep neural networks
S Jha, S Raj, S Fernandes, SK Jha, S Jha, B Jalaian, G Verma, A Swami
Advances in Neural Information Processing Systems 32, 2019
强制性开放获取政策： US National Science Foundation, US Department of Defense
Sherlock-a tool for verification of neural network feedback systems: demo abstract
S Dutta, X Chen, S Jha, S Sankaranarayanan, A Tiwari
Proceedings of the 22nd ACM International Conference on Hybrid Systems …, 2019
强制性开放获取政策： US National Science Foundation
Dehallucinating large language models using formal methods guided iterative prompting
S Jha, SK Jha, P Lincoln, ND Bastian, A Velasquez, S Neema
2023 IEEE International Conference on Assured Autonomy (ICAA), 149-152, 2023
强制性开放获取政策： US Department of Defense
TeLEx: learning signal temporal logic from positive examples using tightness metric
S Jha, A Tiwari, SA Seshia, T Sahai, N Shankar
Formal Methods in System Design 54, 364-387, 2019
强制性开放获取政策： US National Science Foundation, US Department of Defense
A risk-sensitive finite-time reachability approach for safety of stochastic dynamic systems
MP Chapman, J Lacotte, A Tamar, D Lee, KM Smith, V Cheng, JF Fisac, ...
2019 American Control Conference (ACC), 2958-2963, 2019
强制性开放获取政策： US National Science Foundation
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