Mutual learning and spelling in motor imagery brain-computer interfaces

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Deploying energy-efficient deep neural networks on energy-constrained edge devices is an important research topic in both machine learning and circuit design communities. Both artificial neural networks (ANNs) and spiking neural networks (SNNs) have been p ...

Real-time bioaerosol monitoring is improving the quality of life for people affected by allergies, but it often relies on deep learning models which pose challenges for widespread adoption. These models are typically trained in a supervised fashion and req ...

As one of the major threats to women's health worldwide, breast cancer requires early diagnosis and accurate classification, since they are key to optimizing therapeutic interventions and ensuring precise prognosis. Recently, deep learning has demonstrated ...

Differences in acquisition protocols or hardware result in measurable changes in image characteristics. These differences affect distributional properties and can also affect the spatial and temporal characteristics of the images. Likewise, the distributio ...

Many empirical studies have provided evidence for the emergence of algorithmic mechanisms (abilities) in the learning of language models, that lead to qualitative improvements in the model capabilities. Yet, a theoretical characterization of how such mecha ...

FDTD/FEM simulations, strengthened by machine learning, achieve 95.44% optical absorption efficiency in TiO 2 /TiN plasmonic nanocavities for solar energy harvesting. ...

Contemporary AI faces important limitations that remain unresolved despite significant successes. Chief among these are the inability to acquire new knowledge without destroying old, the incomprehensible and nonengineerable nature of internal representatio ...

Facial paralysis is a highly burdening condition, resulting in a patient's inability to move his musculature on one or both sides of the mouth. The restoration of facial movement is crucial for enhancing the overall patients' quality of life. The use of DE ...

Now is an exciting time for the domain of Earth observation (EO), with a multitude of diverse sensors looking at the planet from satellites, airplanes or drones. The volume of imagery acquired is massive, and hold great potential for a variety of applicati ...

We present a reinforcement learning framework for constructing assemblies composed of rigid parts, which are commonly seen in many historical masonry buildings and bridges. Traditional construction methods for such structures often depend on dense scaffold ...

This paper investigates the fundamental regression task of learning k neurons (a.k.a. teachers) from Gaussian input, using two-layer ReLU neural networks with width m (a.k.a. students) and m, k = O(1), trained via gradient descent under proper initializati ...

Sign Language conveys information through multiple channels composed of manual (handshape, hand movement) and non-manual (facial expression, mouthing, body posture) components. Sign language assessment involves giving granular feedback to a learner, in ter ...

Neurons in the human amygdala and hippocampus are classically thought to encode a person’s identity invariant to visual features. However, it remains largely unknown how visual information from higher visual cortical areas is translated into such a semanti ...

High-dimensional data must be highly structured to be learnable. Although the compositional and hierarchical nature of data is often put forward to explain learnability, quantitative measurements establishing these properties are scarce. Likewise, accessin ...

Change detection (CD) is a critical task in remote sensing, especially for monitoring dynamic urban environments. In this work, we present a novel, self-supervised CD approach that leverages a two-player architecture to improve the reliability and accuracy ...

Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their forecast errors are severely limited by the local optimal weight issue in opt ...

This thesis addresses key challenges in developing adaptive lower-limb exoskeletons to enhance balance, mobility, and user autonomy during daily living activities. It presents a comprehensive exploration of three critical aspects: push recovery during stan ...

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

Buildings significantly impact urban energy consumption. Mobile passive solutions, such as manual solar protections, can mitigate heat gains, but their effectiveness depends on occupants’ decisions. Analyzing occupant adjustments of manual systems is chall ...

In today's era of rapid urbanization, smart cities are emerging as a beacon of efficiency and sustainability. At the heart of this evolution is the integration of Machine Learning (ML), which can transform vast streams of data into informed decisions. This ...

Mutual learning and spelling in motor imagery brain-computer interfaces

Chattez avec Graph Search

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

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

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

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

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

Machine-learning-empowered FDTD/FEM simulations for predictive solar energy absorption in plasmonic metamaterial nanocavity arrays

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

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

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

Learning to Assemble with Alternative Plans

How Gradient Descent Balances Features: A Dynamical Analysis For Two-Layer Neural Networks

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

Feature-based encoding of face identity by single neurons in the human amygdala and hippocampus

Probing the latent hierarchical structure of data via diffusion models

Self-supervised Change Detection via Cooperative Learning: A Two-Player Model

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

Partial Assistance with Lower-Limb Exoskeletons to Enhance Gait and Balance in Daily Living Activities

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

Machine-learning to analyze human-building interactions: How do people use mobile solar protections?

From Data to Decision: Exploring Machine Learning's Impact on Shaping Smart Cities