Theory of representation learning in cortical neural networks

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Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to catheteri ...

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

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Theory of representation learning in cortical neural networks

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Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population

Topics in statistical physics of high-dimensional machine learning

Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

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

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

Robust machine learning for neuroscientific inference

Application of Deep Learning and Geospatial Analysis in Soil Loss Risk in the Moulouya Watershed, Morocco

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

A Reconfigurable High-Dynamic Range ∆Σ Front-End with Event-Based Decimation for Bandwidth-Efficient Implantable Neural Interfaces

Random matrix methods for high-dimensional machine learning models

Image steganalysis using active learning and hyperparameter optimization

Fast adaptation to rule switching using neuronal surprise

Edge-Cloud Collaborated Object Detection via Bandwidth Adaptive Difficult-Case Discriminator

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

t-PiNet: A thermodynamics-informed hierarchical learning for discovering constitutive relations of geomaterials

Understanding generalization and robustness in modern deep learning

Self-Supervised Anomaly Segmentation via Diffusion Models with Dynamic Transformer UNet

Safe Deep Neural Networks