NeuroMechFly v2: simulating embodied sensorimotor control in adult <i>Drosophila</i>

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

As urban populations continue to expand and vehicle density increases, the need for effective traffic monitoring and management becomes increasingly critical. Urban areas face significant challenges such as growing congestion, safety concerns, and parking ...

PSI and North Carolina State University are developing a high-resolution multi-physics core solver for Pressurized Water Reactor (PWR) analysis in Cartesian geometry, using the neutron transport code nTRACER and two Machine Learning (ML) models providing t ...

During fear learning, associations between a sensory cue (conditioned stimulus, CS) and an aversive stimulus (unconditioned stimulus, US) are formed in specific brain circuits. The lateral amygdala (LA) is involved in CS-US integration; however, US pathway ...

Recent advancements in neuroscience, wearable technology, and artificial intelligence are paving the way for computing systems that are integrated with the brain and nervous system. Over the past years, we have witnessed the simultaneous progression of wea ...

In this work, we focus on the design of optimal controllers that must comply with an information structure. State-of-the-art approaches do so based on the H2 or H∞ norm to minimize the expected or worst-case cost in the presence of stochastic or adversaria ...

Deep neural networks (DNNs) provide state-of-the-art accuracy for vision tasks, but they require significant resources for training. Thus, they are trained on cloud servers far from the edge devices that acquire the data. This issue increases communication ...

Methods of computational quantum chemistry provide accurate approximations of molecular properties crucial for computer-aided drug discovery and other areas of chemical science. However, high computational complexity limits the scalability of their applica ...

The process of quantifying and analyzing animal behavior involves translating the naturally occurring descriptive language of their actions into machine-readable code. Yet, codifying behavior analysis is often challenging without deep understanding of anim ...

The imaginary-time evolution of quantum states is integral to various fields, ranging from natural sciences to classical optimization or machine learning. Since simulating quantum imaginary-time evolution generally requires storing an exponentially large w ...

Multimetallic nanoparticles are of interest as functional materials due to their highly tunable properties. However, synthesizing congruent mixtures of immiscible components is limited by the need for high-temperature procedures followed by rapid quenching ...

The identification of nanomaterials with the properties required for energy-efficient electronic systems is usually a tedious human task. A workflow to rapidly localize and characterize nanomaterials at the various stages of their integration into large-sc ...

Attention-based architectures have become ubiquitous in machine learning. Yet, our understanding of the reasons for their effectiveness remains limited. This work proposes a new way to understand self-attention networks: we show that their output can be de ...

Gyrification of the cerebral cortex is a developmentally important process, but the mechanisms that drive cortical folding are not fully known. Theories propose that changes within the cortical plate (CP) cause gyrification, yet differences between the CP ...

Described herein are microelectrode array devices, and methods of fabrication and use of the same, to provide highly localized and efficient electrical stimulation of a neurological target. The device includes multiple microelectrode elements arranged alon ...

NeuroMechFly v2: simulating embodied sensorimotor control in adult <i>Drosophila</i>

Chat with Graph Search

Drone-Based Urban Traffic Monitoring and User Behavior Prediction

High-resolution predictions of the coolant properties for the 3D PWR core with artificial neural networks based on CTF

A posterior insula to lateral amygdala pathway transmits US-offset information with a limited role in fear learning

NeuroCHI: Are We Prepared for the Integration of the Brain with Computing?

Closing the Gap to Quadratic Invariance: A Regret Minimization Approach to Optimal Distributed Control

Hierarchical Training of Deep Neural Networks Using Early Exiting

∇2DFT: A Universal Quantum Chemistry Dataset of Drug-Like Molecules and a Benchmark for Neural Network Potentials

AmadeusGPT: a natural language interface for interactive animal behavioral analysis

Stochastic Approximation of Variational Quantum Imaginary Time Evolution

Low-temperature non-equilibrium synthesis of anisotropic multimetallic nanosurface alloys for electrochemical CO2 reduction

High-speed identification of suspended carbon nanotubes using Raman spectroscopy and deep learning

Attention is not all you need: pure attention loses rank doubly exponentially with depth

Genetic and microstructural differences in the cortical plate of gyri and sulci during gyrification in fetal sheep

Implantable probe for stimulating neurological target e.g. neurons and subthalamic nucleus, has several microelectrode elements arranged at distal end of elongated probe shaft, and electrical contact arranged proximally along shaft