NeuralTree: A 256-Channel 0.227-mu J/Class Versatile Neural Activity Classification and Closed-Loop Neuromodulation SoC

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High resolution multi-physics core solvers predict safety parameters on a local scale with high accuracy while simulating local heterogeneities and their consequences. To achieve this, large computational resources are needed which renders the extensive us ...

Building energy modeling plays a vital role in optimizing the operation of building energy systems by providing accurate predictions of the building's real-world conditions. In this context, various techniques have been explored, ranging from traditional p ...

This thesis explores stochastic optimal control through three interconnected contributions: a theoretical framework, and the development of two regression methods, POLK and POLRF, tailored to high-dimensional regression challenges in this domain. In the f ...

Symbolic Regression holds great potential for uncovering underlying mathematical and physical relationships from observed data. However, the vast combinatorial space of possible expressions poses significant challenges for previous online search methods an ...

The barren plateau phenomenon, characterized by loss gradients that vanish exponentially with system size, poses a challenge to scaling variational quantum algorithms. Here we explore the potential of warm starts, whereby one initializes closer to a soluti ...

Much of our knowledge about the brain is derived from extracellular recordings of the electric fields produced by neural activity. However, interpretation of these signals is nontrivial. In par- ticular, it is difficult to link macro-scale observations of ...

Language modeling has seen impressive progress over the last few years. The invention of the Transformer architecture sparked a revolution in many fields of machine learning, including breakthroughs in chemistry and biology. In this chapter, we explore how ...

A dry frictional interface loaded in shear often displays stick–slip. The amplitude of this cycle depends on the probability that a microscopic event nucleates a rupture and on the rate at which microscopic events are triggered. The latter is determined by ...

Neural activity within the ventromedial prefrontal cortex (vmPFC) and anterior insula (aIns) is often associated with economic choices and confidence. However, it remains unclear whether these brain regions are causally related to these processes. To addre ...

Interface stress is a fundamental descriptor for interphase boundaries and is defined in strict relation to the interface energy. In nanomultilayers with their intrinsically high interface density, the functional properties are dictated by the interface st ...

The cerebellum is thought to help detect and correct errors between intended and executed commands(1,2) and is critical for social behaviours, cognition and emotion 3 Computations for motor control must be performed quicklyto correct errors in real time an ...

The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics and given rise to a number of open research questions. One such question is whether it is possible to reconstruct the information stored in ...

Neuroprosthetic devices used for the treatment of lower urinary tract dysfunction, such as incontinence or urinary retention, apply a pre-set continuous, open-loop stimulation paradigm, which can cause voiding dysfunctions due to neural adaptation. In the ...

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as th ...

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative motor disorder, which results in death within a few years of diagnosis. While the cause of most cases of ALS is unknown, 10% of cases are familial (fALS), and associated with mutations in one of ov ...

As modern machine learning continues to achieve unprecedented benchmarks, the resource demands to train these advanced models grow drastically. This has led to a paradigm shift towards distributed training. However, the presence of adversariesâ whether ma ...

A combination of two numerical techniques of computational electromagnetics, namely, method of moments and vector spherical wave expansion, is used to show performance limitations on the radiation efficiency of implantable antennas and to efficiently resol ...

Personality changes following neurosurgical procedures remain poorly understood and pose a major concern for patients, rendering a strong need for predictive biomarkers. Here we report a case of a female patient in her 40s who underwent resection of a larg ...

Cyclic Queuing and Forwarding (CQF) is a mechanism defined by IEEE TSN for providing low jitter in a deterministic network. CQF uses a common time cycle and two buffers per node output port: during one cycle incoming packets are stored in one buffer while ...

Author summaryForecasting the short time evolution of the COVID-19 daily incidence is a key issue in the epidemic decision making policy. We propose a machine learning method which forecasts the future values of the daily incidence trend based on the evolu ...

NeuralTree: A 256-Channel 0.227-mu J/Class Versatile Neural Activity Classification and Closed-Loop Neuromodulation SoC

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High-Resolution Predictions of the Fuel and Cladding Temperatures for the 3D PWR Core with Artificial Neural Networks trained on CTF

Combining physics-based and data-driven modeling for building energy systems

Parsimonious Online Learning with Kernels and Random Features with Applications to Stochastic Optimal Control

Interactive symbolic regression with co-design mechanism through offline reinforcement learning

Variational Quantum Simulation: A Case Study for Understanding Warm Starts

Coupled Electromagnetic-Electrophysiological Modeling of Neural Circuits

Transformers and Large Language Models for Chemistry and Drug Discovery

Armouring of a Frictional Interface by Mechanical Noise

Direct stimulation of anterior insula and ventromedial prefrontal cortex disrupts economic choices

Experimental and ab initio derivation of interface stress in nanomultilayered coatings: Application to immiscible Cu/W system with variable in-plane stress

Structured cerebellar connectivity supports resilient pattern separation

Bayesian reconstruction of memories stored in neural networks from their connectivity

Decoding bladder state from pudendal intraneural signals in pigs

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

The role of the NF-kappaB pathway in Amyotrophic lateral sclerosis pathogenesis

Distributed Optimization with Byzantine Robustness Guarantees

Maximum Radiation Efficiency of an Implantable Antenna: The Role of High-Order Modes

Experimentally-evidenced personality alterations following meningioma resection: A case report

Configuration of Guard Band and Offsets in Cyclic Queuing and Forwarding

Learning from the past: A short term forecast method for the COVID-19 incidence curve