Watermarking-based Defense against Adversarial Attacks on Deep Neural Networks

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Watermarking-based Defense against Adversarial Attacks on Deep Neural Networks

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The topology of a chaotic attractor in the Kuramoto-Sivashinsky equation

Optimizing Dynamic Aperture Studies with Active Learning

On the added value of sequential deep learning for the upscaling of evapotranspiration

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

MetaCap: Meta-learning Priors from Multi-view Imagery for Sparse-View Human Performance Capture and Rendering

On the number of regions of piecewise linear neural networks

Directly optimizing for synthesizability in generative molecular design using retrosynthesis models

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

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

Sparse autoregressive neural networks for classical spin systems

Machine Learning for Modeling Stock Returns

Re-pseudonymization Strategies for Smart Meter Data Are Not Robust to Deep Learning Profiling Attacks

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

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

Aggregating Spatial and Photometric Context for Photometric Stereo

Safe Deep Neural Networks

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Neural Exponential Stabilization of Control-affine Nonlinear Systems

Gibbs sampling the posterior of neural networks