Publications related to Energy Conservation and State-Space Characterization of Adaptive Filter Performance

Distributional Regression and Autoregression via Optimal Transport

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Florent Gérard Krzakala, Lenka Zdeborová, Hugo Chao Cui

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

Distribution-on-distribution regression via optimal transport maps

Victor Panaretos, Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact interval. Our regression model is based on the theory of optimal transportation, and links the conditional Frechet mean of the resp ...

OXFORD UNIV PRESS2022

Minimax rate for optimal transport regression between distributions

Victor Panaretos, Laya Ghodrati

Distribution-on-distribution regression considers the problem of formulating and es-timating a regression relationship where both covariate and response are probability distributions. The optimal transport distributional regression model postulates that th ...

ELSEVIER2022

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Mathias Josef Payer

Fuzzing is the de-facto default technique to discover software flaws, randomly testing programs to discover crashing test cases. Yet, a particular scenario may only care about specific code regions (for, e.g., bug reproduction, patch or regression testing) ...

ASSOC COMPUTING MACHINERY2022

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings

Silvestro Micera, Vincent Alexandre Mendez, Leonardo Pollina, Fiorenzo Artoni

The control of robotic prosthetic hands (RPHs) for upper limb amputees is far from optimal. Simultaneous and proportional finger control of a RPH based on EMG signals is still challenging. Based on EMG and kinematics recordings of subjects following a pre- ...

IEEE2021

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Nikolaos Geroliminis, Emmanouil Barmpounakis

The work proposes a multi-modal regional mean speed regression analysis for the city network of Athens, Greece. The dataset from pNUEMA experiment is used in the present context. Accumulations and mean speeds of different modes are estimated and compared t ...

2021

Gaussian Process Regression for Materials and Molecules

Michele Ceriotti, David Mark Wilkins

We provide an introduction to Gaussian process regression (GPR) machinelearning methods in computational materials science and chemistry. The focus of the present review is on the regression of atomistic properties: in particular, on the construction of in ...

AMER CHEMICAL SOC2021

Model Based Navigation of Delta-Wing UAV - In-Flight Calibration and Autonomous Performance

Jan Skaloud, Gabriel François Laupré, Pasquale Longobardi

This paper presents the first practical results of a model-based approach to autonomous navigation applied to a small delta wing drone. The aerodynamic coefficients of the considered platform are unknown and need to be determined for the (vehicle dynamic) ...

2021

Neural controlled differential equations for crop classification

Accurate and scalable crop classification is important for food security and sustainable resources management. The temporal development of crops, i.e., their phenology, is a continuous phenomena that if properly captured, can help to discern them. The nove ...

2021

Energy Conservation and State-Space Characterization of Adaptive Filter Performance

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Distributional Regression and Autoregression via Optimal Transport

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Distribution-on-distribution regression via optimal transport maps

Minimax rate for optimal transport regression between distributions

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Gaussian Process Regression for Materials and Molecules

Model Based Navigation of Delta-Wing UAV - In-Flight Calibration and Autonomous Performance

Neural controlled differential equations for crop classification

Distributional Regression and Autoregression via Optimal Transport

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Distribution-on-distribution regression via optimal transport maps

Gaussian Process Regression for Materials and Molecules

Neural controlled differential equations for crop classification

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Minimax rate for optimal transport regression between distributions

Model Based Navigation of Delta-Wing UAV - In-Flight Calibration and Autonomous Performance

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings