Geometry-Aware Deep Recurrent Neural Networks for Hyperspectral Image Classification

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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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In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

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Machine learning and artificial intelligence methods have achieved remarkable success, matching and even surpassing human capabilities in various complex tasks. However, many demonstrations have generally neglected a critical part of the intelligence that ...

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Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

Many feedforward neural networks (NNs) generate continuous and piecewise-linear (CPWL) mappings. Specifically, they partition the input domain into regions on which the mapping is affine. The number of these so-called linear regions offers a natural metric ...

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The mammalian brain develops through precisely orchestrated events that transform a simple neural tube into a complex structure. While single-cell RNA sequencing has revealed remarkable cellular heterogeneity, the lack of spatial context limits our underst ...

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

The process of protein aggregation, central to neurodegenerative diseases like Huntington’s, is challenging to study due to its unpredictable nature and relatively rapid kinetics. Understanding its biomechanics is crucial for unraveling its role in disease ...

Transformer models such as GPT generate human-like language and are predictive of human brain responses to language. Here, using functional-MRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict t ...

Geometry-Aware Deep Recurrent Neural Networks for Hyperspectral Image Classification

Chattez avec Graph Search

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SaliencyMix plus : Noise-Minimized Image Mixing Method With Saliency Map in Data Augmentation

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

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

Sequential Reasoning with Socially Caused Beliefs

Weighting Pseudo-labels via High-Activation Feature Index Similarity and Object Detection for Semi-supervised Segmentation

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

On the number of regions of piecewise linear neural networks

Factor-graph Optimisation with Vehicle Dynamic Models for Mapping & Sensing Applications

Overcoming Distribution Shifts and Imbalance Challenges in Representation Learning for Deep Regression Models

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Bulk measurement of membrane permeability for random cyclic peptides in living cells to guide drug development

Fine-grained mapping of neural progenitors subtypes in the embryonic brain unveils context-dependent roles of signalling on cell fate decisions

Optimizing Dynamic Aperture Studies with Active Learning

Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging

Driving and suppressing the human language network using large language models