Pixel Art
Published:
Small project using C++ and SFML to depixelize pixel art.
Posts by Tags
2D Graphics
3D Graphics
3D Graphics with OpenGL
Published:
Small project using the OpenGL library to draw a complex 3D scene.
C++
Pixel Art
Published:
Small project using C++ and SFML to depixelize pixel art.
3D Graphics with OpenGL
Published:
Small project using the OpenGL library to draw a complex 3D scene.
Elliptic Curve Cryptography
Published:
Mini project studying elliptic curves on finite field, from basic properties to Hasse theorem and Schoof’s algorithm. Accompanying C++ library with GMP implementing these results.
Deep learning
Robustness in Neural ODEs and SDEs
Published:
Recent studies show that Neural ODEs are more robust against adversarial attacks than traditional DNNs, but as complexity increases, concerns about robustness and expressivity arise, prompting exploration of stochastic noise regularization.
Kaggle
Forest Classification - Kaggle Challenge
Published:
This Kaggle challenge involved a classification problem (with 7 different classes) based on a dataset of forest parcels. The data consisted of 55 columns, including 11 numerical variables and 2 categorical variables (with 4 and 40 classes, respectively). To tackle this problem, we employed strategies detailed chronologically in this report. After an initial data exploration phase and attempts at dimensionality reduction, we tested several classic algorithms and proceeded with optimizations where possible.
OpenGL
3D Graphics with OpenGL
Published:
Small project using the OpenGL library to draw a complex 3D scene.
Optimal Transport
An Alternative to the Log-Likelihood with Entropic Optimal Transport
Published:
This paper explores the entropic optimal transport (EOT) loss and its estimator in parameter estimation, comparing its advantages over traditional likelihood methods, such as improved robustness, faster convergence, and resilience to bad local optima, with a focus on theoretical justification and experimental validation in Gaussian Mixture Models.
Parameter Estimation
An Alternative to the Log-Likelihood with Entropic Optimal Transport
Published:
This paper explores the entropic optimal transport (EOT) loss and its estimator in parameter estimation, comparing its advantages over traditional likelihood methods, such as improved robustness, faster convergence, and resilience to bad local optima, with a focus on theoretical justification and experimental validation in Gaussian Mixture Models.
SDE
Robustness in Neural ODEs and SDEs
Published:
Recent studies show that Neural ODEs are more robust against adversarial attacks than traditional DNNs, but as complexity increases, concerns about robustness and expressivity arise, prompting exploration of stochastic noise regularization.
Spectral methods
Spectral Methods for Clustering in Finance
Published:
This report gathers tools from spectral graph theory to analyze stock market relation graphs, focusing on spectral embedding for positioning companies in Euclidean space and exploring graph entropy to classify graphs and detect regime changes, with a generalization to directed weighted graphs and in-depth explanations of the underlying concepts and algorithms.
Statistics
An Alternative to the Log-Likelihood with Entropic Optimal Transport
Published:
This paper explores the entropic optimal transport (EOT) loss and its estimator in parameter estimation, comparing its advantages over traditional likelihood methods, such as improved robustness, faster convergence, and resilience to bad local optima, with a focus on theoretical justification and experimental validation in Gaussian Mixture Models.
TDA
Discrete Morse Theory for Relative Cosheaf Homology
Published:
This paper aims to generalize discrete Morse theory in the context of relative cosheaf homology on filtrations of finite simplicial complexes, enabling faster computations. These methods are extended to persistent cosheaf homology for longer filtrations.
cryptography
Elliptic Curve Cryptography
Published:
Mini project studying elliptic curves on finite field, from basic properties to Hasse theorem and Schoof’s algorithm. Accompanying C++ library with GMP implementing these results.
elliptic curves
Elliptic Curve Cryptography
Published:
Mini project studying elliptic curves on finite field, from basic properties to Hasse theorem and Schoof’s algorithm. Accompanying C++ library with GMP implementing these results.
neural ODEs
Robustness in Neural ODEs and SDEs
Published:
Recent studies show that Neural ODEs are more robust against adversarial attacks than traditional DNNs, but as complexity increases, concerns about robustness and expressivity arise, prompting exploration of stochastic noise regularization.