Adaptive hot water production based on Supervised Learning

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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 ...

Training data mixtures greatly impact the generalization performance of large language models. Existing domain reweighting methods often rely on costly weight computations and require retraining when new data is introduced. To this end, we introduce a flex ...

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

Low-light photography produces images with low signal-to-noise ratios due to limited photons. In such conditions, common approximations like the Gaussian noise model fall short, and many denoising techniques fail to remove noise effectively. Although deep- ...

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 ...

Buildings play a pivotal role in the ongoing worldwide energy transition, accounting for 30% of the global energy consumption. With traditional engineering solutions reaching their limits to tackle such large-scale problems, data-driven methods and Machine ...

Implicit neural representations map a shape-specific latent code and a 3D coordinate to its corresponding signed distance (SDF) value. However, this approach only offers a single level of detail. Emulating low levels of detail can be achieved with shallow ...

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 ...

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 ...

Radiant floor heating is widely recognized for its low-energy consumption and high efficiency. Traditional systems, however, typically heat the entire floor area within a space, conditioning spaces uniformly regardless of occupancy. This study investigates ...

Access to water and sanitation are major issues for many West African cities, especially for low- and middle-income nations like Mauritania. This study investigates the socioeconomic, demographic, and geographical factors influencing household water access ...

Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of more renewable energy sources into the power grid. PV power production is highly intermittent, due to the stochastic cloud behaviour and cloud dynamics. Previous w ...

Unmanned vehicles have become indispensable tools in various fields such as agriculture, environmental monitoring, and disaster response. A crucial component of these platforms is sensor fusion. As measurements are inherently noisy, certain variables canno ...

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

Sharing data across institutions for genome-wide association studies (GWAS) would enhance the discovery of genetic variation linked to health and disease1,2. However, existing data-sharing regulations limit the scope of such collaborations3. Although crypt ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

Web search engines process billions of queries daily, making the balance between computational efficiency and ranking quality crucial. While neural ranking models have shown impressive performance, their computational costs, particularly in feature extract ...

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 ...

Adaptive hot water production based on Supervised Learning

Chattez avec Graph Search

On the number of regions of piecewise linear neural networks

CHAMELEON: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning

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

Dark Noise Diffusion: Noise Synthesis for Low-Light Image Denoising

Sequential Reasoning with Socially Caused Beliefs

Fusing Pre-existing Knowledge and Machine Learning for Enhanced Building Thermal Modeling and Control

A Latent Implicit 3D Shape Model for Multiple Levels of Detail

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

Incorporating Projective Geometry into Deep Learning

Modular Radiant Floor Heating and its Effect on Local Thermal Comfort

Water for all: determinants of household water access in Nouakchott, Mauritania

Network time series forecasting in photovoltaics power production

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

Aggregating Spatial and Photometric Context for Photometric Stereo

Secure and federated genome-wide association studies for biobank-scale datasets

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Cost-Efficiency Trade-offs for Neural Cascade Rankers in Web Search

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