The Anatomy of a Cryptocurrency Pump-and-Dump Scheme

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Poisoning attacks compromise the training data utilized to train machine learning (ML) models, diminishing their overall performance, manipulating predictions on specific test samples, and implanting backdoors. This article thoughtfully explores these atta ...

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The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation ...

The way biological brains carry out advanced yet extremely energy efficient signal processing remains both fascinating and unintelligible. It is known however that at least some areas of the brain perform fast and low-cost processing relying only on a smal ...

This work introduces DiGress, a discrete denoising diffusion model for generating graphs with categorical node and edge attributes. Our model utilizes a discrete diffusion process that progressively edits graphs with noise, through the process of adding or ...

With the recent advent of blockchains, we have witnessed a plethora of blockchain proposals. These proposals range from using work to using time, storage or stake in order to select blocks to be appended to the chain. As a drawback it makes it difficult fo ...

Multiple sclerosis (MS) is the most common demyelinating disease of the central nervous system and affects almost 3 million people worldwide. There is currently no cure for MS, and its symptoms, starting with fatigue and weakness, often progress over time ...

This thesis addresses theoretical and practical aspects of identification and subsequent control of self-exciting point processes. The main contributions correspond to four separate scientific papers. In the first paper, we address the challenge of robust ...

Advances in mobile computing have paved the way for new types of distributed applications that can be executed solely by mobile devices on Device-to-Device (D2D) ecosystems (e.g., crowdsensing). Sophisticated applications, like cryptocurrencies, need distr ...

Knowledge of the oxidation state of metal centres in compounds and materials helps in the understanding of their chemical bonding and properties. Chemists have developed theories to predict oxidation states based on electron-counting rules, but these can f ...

The advances made in predicting visual saliency using deep neural networks come at the expense of collecting large-scale annotated data. However, pixel-wise annotation is labor-intensive and overwhelming. In this paper, we propose to learn saliency predict ...

We propose an optical proof-of-work scheme that feeds data encoded into wavelength-division multiplexed modes through a programmable photonic network. We verify robustness by modeling network dispersion, allowing for energy-efficient optical alternatives t ...

The inverse dynamics of a robotic manipulator is instrumental in precise robot control and manipulation. However, acquiring such a model is challenging, not only due to unmodelled non-linearities such as joint friction, but also from a machine learning per ...

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We construct a ‘reflexivity’ index to measure the activity generated endogenously within a market for cryptocurrencies. For this purpose, we fit a univariate self-exciting Hawkes process with two classes of parametric kernels to high-frequency trading data ...

We conduct a detailed analysis of investors in successful initial coin offerings (ICOs). The average ICO has 4700 contributors. The median participant contributes small amounts and many investors sell their tokens before the underlying product is developed ...

Stereo reconstruction is a problem of recovering a 3d structure of a scene from a pair of images of the scene, acquired from different viewpoints. It has been investigated for decades and many successful methods were developed. The main drawback of these ...

Cardiac and aortic characteristics are crucial for cardiovascular disease detection. However, noninvasive estimation of aortic hemodynamics and cardiac contractility is still challenging. This paper investigated the potential of estimating aortic systolic ...

This thesis consists of three chapters that study separate subjects in the area of corporate governance and financial intermediation. In the first chapter, I study a protectionist anti-takeover law introduced in 2014 in France that covers a subset of all ...

The Anatomy of a Cryptocurrency Pump-and-Dump Scheme

Chattez avec Graph Search

Machine Learning Security Against Data Poisoning: Are We There Yet?

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DiGress: Discrete Denoising diffusion for graph generation

DIABLO: A Benchmark Suite for Blockchains

Deep learning-based analysis of multiple sclerosis lesions with high and ultra-high field MRI

Self-Exciting Point Processes: Identification and Control

Toward Mobile Distributed Ledgers

Using collective knowledge to assign oxidation states of metal cations in metal-organic frameworks

Learning Saliency From Single Noisy Labelling: A Robust Model Fitting Perspective

Wavelength-Division Multiplexed Optical Cryptocurrency

Efficient Configuration Exploration in Inverse Dynamics Acquisition of Robotic Manipulators

Datasets and Models for Historical Newspaper Article Segmentation

Quantifying Endogeneity of Cryptocurrency Markets

ICO investors

Learning stereo reconstruction with deep neural networks

Noninvasive estimation of aortic hemodynamics and cardiac contractility using machine learning

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