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How Does Pre-Trained Wav2Vec 2.0 Perform On Domain-Shifted Asr? An Extensive Benchmark On Air Traffic Control Communications

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How Does Pre-Trained Wav2Vec 2.0 Perform On Domain-Shifted Asr? An Extensive Benchmark On Air Traffic Control Communications

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Self-supervised and few-shot learning for robust bioaerosol monitoring

Interact with Earth Observation Images using AI: Transparent Methods and Evaluation for Visual Question Answering

Foundations of a New Learning Paradigm in AI Grounded in the Principles of Evolutionary Developmental Biology

Eflop: a Sparsity-aware Metric for Evaluating Computational Cost in Spiking and Non-spiking Neural Networks

Posterior-Based Analysis of Spatio-Temporal Features for Sign Language Assessment

Robust machine learning for neuroscientific inference

A Closer Look at Benchmarking Self-supervised Pre-training with Image Classification

Mspo: a Machine Learning Hyperparameter Optimization Method for Enhanced Breast Cancer Image Classification

A continuous-wave and pulsed X-band electron spin resonance spectrometer operating in ultra-high vacuum for the study of low dimensional spin ensembles

A phase transition between positional and semantic learning in a solvable model of dot-product attention

Lotic-SIPCO2: Adaptation of an open-source CO2 sensor system and examination of associated emission uncertainties across a range of stream sizes and land uses

Probing the latent hierarchical structure of data via diffusion models

Technology-Aware Logic Synthesis for Superconducting Electronics

DEMO: Dielectric elastomer actuators (DEAs) for the restoration of facial movements

Predicting Visual Stimuli From Cortical Response Recorded With Wide-Field Imaging in a Mouse

Domain shift, domain adaptation, and generalization: A focus on MRI

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Context selectivity with dynamic availability enables lifelong continual learning

In-Sensor Passive Speech Classification with Phononic Metamaterials

Improving the accuracy and interpretability of neural networks for wind power forecasting