Publications related to Towards goal-driven deep neural network models to elucidate human arm proprioception

Regularization of polynomial networks for image recognition

Volkan Cevher, Grigorios Chrysos, Bohan Wang

Deep Neural Networks (DNNs) have obtained impressive performance across tasks, however they still remain as black boxes, e.g., hard to theoretically analyze. At the same time, Polynomial Networks (PNs) have emerged as an alternative method with a promising ...

2023

Novel Design and Implementation of a Neuromuscular Controller on a Hip Exoskeleton for Partial Gait Assistance

Auke Ijspeert, Mohamed Bouri, Ali Reza Manzoori, Andrea Di Russo, Sara Messara

Exoskeletons intended for partial assistance of walking should be able to follow the gait pattern of their users, via online adaptive control strategies rather than imposing predefined kinetic or kinematic profiles. NeuroMuscular Controllers (NMCs) are ada ...

2023

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Sabine Süsstrunk, Mathieu Salzmann, Yulun Jiang, Chen Liu, Zhuoyi Huang

We address the problem of stably and efficiently training a deep neural network robust to adversarial perturbations bounded by an

l_1

norm. We demonstrate that achieving robustness against

l_1

-bounded perturbations is more challenging than in the

l_2

...

2023

Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring

Christian Leinenbach, Sergey Shevchik, Rafal Wróbel, Marc Leparoux

This study presents a self-supervised Bayesian Neural Network (BNN) framework using air-borne Acoustic Emission (AE) to identify different Laser Powder Bed Fusion (LPBF) process regimes such as Lack of Fusion, conduction mode, and keyhole without ground-tr ...

London2023

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Mathias Josef Payer, Zhiyao Feng, Chunmin Zhang, Ji Shi

Knowledge of a program's input format is essential for effective input generation in fuzzing. Automated input format reverse engineering represents an attractive but challenging approach to learning the format. In this paper, we address several challenges ...

Berkeley2023

Robust direct acoustic impedance control using two microphones for mixed feedforward-feedback controller

Hervé Lissek, Maxime Volery, Xinxin Guo

This paper presents an acoustic impedance control architecture for an electroacoustic absorber combining both feedforward and feedback microphone-based strategies on a current-driven loudspeaker. Feedforward systems enable good performance for direct imped ...

EDP SCIENCES S A2023

Heterogeneity and developmental dynamics of mammalian neocortical progenitors

Gioele La Manno, Antonio Herrera Camacho, Leila Haj Abdullah Alieh

The central nervous system develops from a pool of neural progenitors which, depending on their location and time of division, generate cells committed to differentiate into specific kinds of neurons or glia. In the last decades, the developmental neurobio ...

Amsterdam2023

Estimating muscle activation from EMG using deep learning-based dynamical systems models

Objective. To study the neural control of movement, it is often necessary to estimate how muscles are activated across a variety of behavioral conditions. One approach is to try extracting the underlying neural command signal to muscles by applying latent ...

2022

Robustness and invariance properties of image classifiers

Apostolos Modas

Deep neural networks have achieved impressive results in many image classification tasks. However, since their performance is usually measured in controlled settings, it is important to ensure that their decisions remain correct when deployed in noisy envi ...

EPFL2022

Essays in Empirical Asset Pricing

Alexis Arilès Marchal

This thesis consists of three applications of machine learning techniques to empirical asset pricing.In the first part, which is co-authored work with Oksana Bashchenko, we develop a new method that detects jumps nonparametrically in financial time series ...

EPFL2022

Towards goal-driven deep neural network models to elucidate human arm proprioception

Graph Chatbot

Chat with Graph Search

Regularization of polynomial networks for image recognition

Novel Design and Implementation of a Neuromuscular Controller on a Hip Exoskeleton for Partial Gait Assistance

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Robust direct acoustic impedance control using two microphones for mixed feedforward-feedback controller

Heterogeneity and developmental dynamics of mammalian neocortical progenitors

Estimating muscle activation from EMG using deep learning-based dynamical systems models

Robustness and invariance properties of image classifiers

Essays in Empirical Asset Pricing

Regularization of polynomial networks for image recognition

Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring

Robust direct acoustic impedance control using two microphones for mixed feedforward-feedback controller

Heterogeneity and developmental dynamics of mammalian neocortical progenitors

Estimating muscle activation from EMG using deep learning-based dynamical systems models

Robustness and invariance properties of image classifiers

Essays in Empirical Asset Pricing

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Novel Design and Implementation of a Neuromuscular Controller on a Hip Exoskeleton for Partial Gait Assistance