CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

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In this thesis, we study two closely related directions: robustness and generalization in modern deep learning. Deep learning models based on empirical risk minimization are known to be often non-robust to small, worst-case perturbations known as adversari ...

Bird's eye view (BEV) representation has emerged as a dominant solution for describing 3D space in autonomous driving scenarios. However, objects in the BEV representation typically exhibit small sizes, and the associated point cloud context is inherently ...

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This dataset contains a collection of ultrafast ultrasound acquisitions from nine volunteers and the CIRS 054G phantom. For a comprehensive understanding of the dataset, please refer to the paper: Viñals, R.; Thiran, J.-P. A KL Divergence-Based Loss for In ...

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Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

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Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

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Understanding generalization and robustness in modern deep learning

IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detection

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (1/6)

Toward universal cell embeddings: integrating single-cell RNA-seq datasets across species with SATURN

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (2/6)

Partial discharge localization in power transformer tanks using machine learning methods

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

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (3/6)

On the Generalization of Stochastic Gradient Descent with Momentum

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (4/6)

GELEX: Generative AI-Hybrid System for Example-Based Learning

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (5/6)

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (6/6)

Machine Learning for Modeling Stock Returns

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Predicting the long-term collective behaviour of fish pairs with deep learning

Residual-based attention in physics-informed neural networks