Bayesian Inversion for Nonlinear Imaging Models Using Deep Generative Priors

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Bayesian Inversion for Nonlinear Imaging Models Using Deep Generative Priors

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

Optimizing Dynamic Aperture Studies with Active Learning

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Robust machine learning for neuroscientific inference

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M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems

Incorporating Projective Geometry into Deep Learning

Residual-based attention in physics-informed neural networks

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

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

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms