Robuta

https://arxiv.org/abs/2103.01018 [2103.01018] Secure UAV Random Networks With Minimum Safety Distance Abstract page for arXiv paper 2103.01018: Secure UAV Random Networks With Minimum Safety Distance random networks210301018secureuav https://research.google/pubs/rawms-random-walk-based-lightweight-membership-service-for-wireless-ad-hoc-networks/ RaWMS - Random Walk based Lightweight Membership Service for Wireless Ad Hoc Networks random walkmembership service https://arxiv.org/abs/2009.08889 [2009.08889] Large Deviations Approach to Random Recurrent Neuronal Networks: Parameter Inference... Abstract page for arXiv paper 2009.08889: Large Deviations Approach to Random Recurrent Neuronal Networks: Parameter Inference and Fluctuation-Induced... large deviations https://openreview.net/forum?id=974ojuN0jU&referrer=%5Bthe%20profile%20of%20Lyudmila%20Grigoryeva%5D(%2Fprofile%3Fid%3D~Lyudmila_Grigoryeva1) RandNet-Parareal: a time-parallel PDE solver using Random Neural Networks | OpenReview Parallel-in-time (PinT) techniques have been proposed to solve systems of time-dependent differential equations by parallelizing the temporal domain. Among... a time https://www.atlantis-press.com/proceedings/iccnce-13/6520 Emergence of High clustering in Random Evolving Networks | Atlantis Press To find the formation mechanism of the complex network possess high clustering property, the paper proposes a new network model based on the neighboring nodes... evolving networksemergencehighclusteringrandom https://jmlr.org/papers/v26/23-0832.html Random Pruning Over-parameterized Neural Networks Can Improve Generalization: A Training Dynamics... neural networks https://arxiv.org/abs/2106.08900v1 [2106.08900v1] Random feature neural networks learn Black-Scholes type PDEs without curse of... Abstract page for arXiv paper 2106.08900v1: Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionality https://arxiv.org/abs/1402.0740 [1402.0740] Exact Free Energies of Statistical Systems on Random Networks Abstract page for arXiv paper 1402.0740: Exact Free Energies of Statistical Systems on Random Networks 1402exactfreeenergies https://openreview.net/forum?id=97GRqCwnJI Training Differentially Private Graph Neural Networks with Random Walk Sampling | OpenReview Deep learning models are known to put the privacy of their training data at risk, which poses challenges for their safe and ethical release to the public.... graph neural networksrandom walktrainingprivate https://www.mdpi.com/2227-7390/9/5/508 A Poisson Process-Based Random Access Channel for 5G and Beyond Networks The 5th generation (5G) wireless networks propose to address a variety of usage scenarios, such as enhanced mobile broadband (eMBB), massive machine-type... a poisson processrandom access channel https://deepai.org/publication/ensemble-in-one-learning-ensemble-within-random-gated-networks-for-enhanced-adversarial-robustness Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness... Mar 27, 2021 - 03/27/21 - Adversarial attacks have rendered high security risks on modern deep learning systems. Adversarial training can significantly enha... https://www.mdpi.com/2073-8994/15/11/1971 Statistical Analyses of a Class of Random Cyclooctatetraene Chain Networks with Respect to Several... In recent years, the research on complex networks has created a boom. The objective of the present paper is to study a random cyclooctatetraene chain whose... https://arxiv.org/abs/2310.19285 [2310.19285] Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes Abstract page for arXiv paper 2310.19285: Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes graph neural networks https://openreview.net/forum?id=vWhUQXQoFF¬eId=Xdhxgs68YI Learning and Aligning Structured Random Feature Networks | OpenReview Artificial neural networks (ANNs) are considered "black boxes'' due to the difficulty of interpreting their learned weights. While choosing the best features... random featurelearningaligningstructurednetworks https://arxiv.org/abs/2106.03970 [2106.03970] Batch Normalization Orthogonalizes Representations in Deep Random Networks Abstract page for arXiv paper 2106.03970: Batch Normalization Orthogonalizes Representations in Deep Random Networks batch normalizationin deep210603970representations https://arxiv.org/abs/math/0305160 [math/0305160] Optimal Nonlinear Prediction of Random Fields on Networks Abstract page for arXiv paper math/0305160: Optimal Nonlinear Prediction of Random Fields on Networks random fieldsmathoptimalnonlinearprediction https://deepai.org/publication/a-method-for-computing-inverse-parametric-pde-problems-with-random-weight-neural-networks A Method for Computing Inverse Parametric PDE Problems with Random-Weight Neural Networks | DeepAI Oct 9, 2022 - 10/09/22 - We present a method for computing the inverse parameters and the solution field to inverse parametric PDEs based on randomized neu...