Oral presentations

Posters

Derivatives of Stochastic Gradient Descent in parametric optimization

Derivatives of Stochastic Gradient Descent in parametric optimization

NeurIPS 2024

One-step differentiation of iterative algorithms

One-step differentiation of iterative algorithms

NeurIPS 2023 (Spotlight)

What functions can GNNs compute on random graphs? The role of Positional Encodings

What functions can GNNs compute on random graphs? The role of Positional Encodings

NeurIPS 2023

On the Robustness of Text Vectorizers

On the Robustness of Text Vectorizers

ICML 2023

Automatic differentiation of nonsmooth iterative algorithms

Automatic differentiation of nonsmooth iterative algorithms

NeurIPS 2022

A framework for bilevel optimization that enables stochastic and global variance reduction algorithms

A framework for bilevel optimization that enables stochastic and global variance reduction algorithms

NeurIPS 2022 (Oral)

On the Universality of Graph Neural Networks on Large Random Graphs

On the Universality of Graph Neural Networks on Large Random Graphs

NeurIPS 2021

Convergence and Stability of Graph Convolutional Networks on Large Random Graphs

Convergence and Stability of Graph Convolutional Networks on Large Random Graphs

NeurIPS 2020 (Spotlight)

Exploiting regularity in sparse Generalized Linear Models

Exploiting regularity in sparse Generalized Linear Models

SPARS 2019