Spiking Neural Networks for Active Time-Resolved SPAD Imaging

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.

Can spiking neural networks (SNNs) approximate the dynamics of recurrent neural networks? Arguments in classical mean-field theory based on laws of large numbers provide a positive answer when each neuron in the network has many “duplicates”, i.e., other n ...

CO2 conversion plays a vital role in addressing climate change by cutting greenhouse gas emissions and promoting a circular carbon economy. Rather than releasing carbon dioxide into the atmosphere, carbon dioxide recycling technologies allows transformatio ...

This paper investigates the problem of load-sharing optimization of gas compressors in the presence of uncertainty. The objective is to operate a set of compressor units in an energy-efficient way, while at the same time meeting a varying load demand. The ...

The macroscopic dynamics of large populations of neurons can be mathematically analyzed using low-dimensional firing-rate or neural-mass models. However, these models fail to capture spike synchronization effects and nonstationary responses of the populati ...

One of the paramount challenges in neuroscience is to understand the dynamics of individual neurons and how they give rise to network dynamics when interconnected. Historically, researchers have resorted to graph theory, statistics, and statistical mechani ...

Transportation electrification is increasing and recently more focus has been directed on heavy vehicles and especially on city buses. Battery electric buses are inherently more energy efficient than diesel buses and the efficiency can be further increased ...

An important feature of the nervous system is its ability to adapt to new stimuli. This adaptation allows for optimal encoding of the incoming information by dynamically changing the coding strategy based upon the incoming inputs to the neuron. At the leve ...

The ability to learn and perform statistical inference with biologically plausible recurrent networks of spiking neurons is an important step toward understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent sp ...

Identifying the structure and dynamics of synaptic interactions between neurons is the first step to understanding neural network dynamics. The presence of synaptic connections is traditionally inferred through the use of targeted stimulation and paired re ...

The selection of a fenestration system for a building is critical, as it impacts energy performance, occupant comfort, and ambiance of a space. Complex Fenestration Systems (CFS) address these criteria using a wide variety of novel technologies but are dif ...

We propose a single source reliable broadcasting algorithm for linear grid-based networks where a message is guaranteed to be delivered to all the nodes of the network. The nodes are mobile and can move from one grid point to another. The solution does not ...

The storage system in this paper is made of supercapacitors. The main goal is to ensure an efficient energy management in a series hybrid vehicle, even if braking resistors are still needed. Design considerations are discussed. In particular the influence ...

We give an overview of the EPFL indoor flying project, whose goal is to evolve neural controllers for autonomous, adaptive, indoor micro-flyers. Indoor flight is still a challenge because it requires miniaturization, energy efficiency, and control of non-l ...

Spiking Neural Networks for Active Time-Resolved SPAD Imaging

Chat with Graph Search

Emergent Rate-Based Dynamics in Duplicate-Free Populations of Spiking Neurons

Low-Power Tunable Micro-Plasma Devices for Efficient and Scalable CO2 Conversion

Real-time optimization of load sharing for gas compressors in the presence of uncertainty

Low-dimensional firing-rate dynamics for populations of renewal-type spiking neurons

Topological exploration of artificial neuronal network dynamics

Different approaches to improve energy consumption of battery electric buses

A new Mathematical Framework to Understand Single Neuron Computations

Stochastic variational learning in recurrent spiking networks

Successful Reconstruction of a Physiological Circuit with Known Connectivity from Spiking Activity Alone

Practical and Policy-Relevant Performance Metrics for Complex Fenestration Systems

Reliable Broadcast in Wireless Mobile Ad Hoc Networks

Design and Control of a Supercapacitor Storage System for Traction Applications

From Wheels to Wings with Evolutionary Spiking Neurons