Cryptanalysis of an E0-like Combiner with Memory

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Cryptanalysis of an E0-like Combiner with Memory

Chat with Graph Search

Partial discharge localization in power transformer tanks using machine learning methods

Random matrix methods for high-dimensional machine learning models

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Graph generative deep learning models with an application to circuit topologies

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Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Novel theory and potential applications of central diastolic pressure decay time constant

Aggregating Spatial and Photometric Context for Photometric Stereo

Robust NAS under adversarial training: benchmark, theory, and beyond

Side-channel analysis of isogeny-based key encapsulation mechanisms and hash-based digital signatures

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Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

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Dynamical Low-Rank Approximation for Stochastic Differential Equations

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

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Deep Learning Generalization with Limited and Noisy Labels