Publications associées à Bio-inspired computing

From event-based surprise to lifelong learning. A journey in the timescales of adaptation

Humans and animals constantly adapt to their environment over the course of their life. This thesis seeks to integrate various timescales of adaptation, ranging from the adaptation of synaptic connections between spiking neurons (milliseconds), rapid behav ...

EPFL2023

A theory of memory consolidation and synaptic pruning in cortical circuits

Georgios Iatropoulos

Over the course of a lifetime, the human brain acquires an astonishing amount of semantic knowledge and autobiographical memories, often with an imprinting strong enough to allow detailed information to be recalled many years after the initial learning exp ...

EPFL2023

Puppeteer and Marionette: Learning Anticipatory Quadrupedal Locomotion Based on Interactions of a Central Pattern Generator and Supraspinal Drive

Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

Quadruped animal locomotion emerges from the interactions between the spinal central pattern generator (CPG), sensory feedback, and supraspinal drive signals from the brain. Computational models of CPGs have been widely used for investigating the spinal co ...

IEEE2023

Neuromorphic computing based on halide perovskites

Mohammad Khaja Nazeeruddin, Feng Gao

Neuromorphic computing requires electronic systems that can perform massively parallel computational tasks with low energy consumption. Such systems have traditionally been based on complementary metal-oxide-semiconductor circuits, but further advances in ...

Nature Portfolio2023

Dense Image-based Predictions for Comics Analysis

Deblina Bhattacharjee

Dense image-based prediction methods have advanced tremendously in recent years. Their remarkable development has been possible due to the ample availability of real-world imagery. While these methods work well on photographs, their abilities do not genera ...

EPFL2023

Controllability and Interpretability in Affective Speech Synthesis

Bastian Schnell

Thanks to Deep Learning Text-To-Speech (TTS) has achieved high audio quality with large databases. But at the same time the complex models lost any ability to control or interpret the generation process. For the big challenge of affective TTS it is infeasi ...

EPFL2022

The spectral bias of polynomial neural networks

Volkan Cevher, Grigorios Chrysos, Leello Tadesse Dadi, Moulik Choraria

Polynomial neural networks (PNNs) have been recently shown to be particularly effective at image generation and face recognition, where high-frequency information is critical. Previous studies have revealed that neural networks demonstrate a spectral bias ...

2022

Micromechanically inspired investigation of cemented granular materials: part I-from X-ray micro tomography to measurable model variables

Gioacchino Viggiani, Edward Carlo Giorgio Andò

Cemented granular materials are abundant in nature and are often artificially produced. Their macroscopic behaviour is driven by small-scale material processes, which are generally classified as: grain breakage, cement damage and fragment rearrangement. Th ...

SPRINGER HEIDELBERG2022

Approximating Relu Networks By Single-Spike Computation

Wulfram Gerstner, Stanislaw Andrzej Wozniak, Ana Stanojevic, Evangelos Eleftheriou, Giovanni Cherubini, Angeliki Pantazi

Developing energy-saving neural network models is a topic of rapidly increasing interest in the artificial intelligence community. Spiking neural networks (SNNs) are biologically inspired models that strive to leverage the energy efficiency stemming from a ...

IEEE2022

Coupled VO2 oscillators circuit as analog first layer filter in convolutional neural networks

Mihai Adrian Ionescu, Kirsten Emilie Moselund, Siegfried Karg, Elisabetta Corti

In this work we present an in-memory computing platform based on coupled VO2 oscillators fabricated in a crossbar configuration on silicon. Compared to existing platforms, the crossbar configuration promises significant improvements in terms of area densit ...

2021