Giulia Luise - RankMe

24 papers A* 8A 1Journal 13Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Accurate and scalable exchange-correlation with deep learning. CoRR Giulia Luise, Chin-Wei Huang, Thijs Vogels, Derk P. Kooi, Sebastian Ehlert, Stephanie Lanius, Klaas J. H. Giesbertz, Amir Karton, Deniz Gunceler, Megan Stanley, Wessel P. Bruinsma, Lin Huang, Xinran Wei, José Garrido Torres, Abylay Katbashev, Rodrigo Chavez Zavaleta, Bálint Máté, Sékou-Oumar Kaba, Roberto Sordillo, Yingrong Chen, David B. Williams-Young, Christopher M. Bishop, Jan Hermann, Rianne van den Berg, Paola Gori-Giorgi
2024	—	`conf`	Bag of Policies for Distributional Deep Exploration. Epi UAI Asen Nachkov, Luchen Li, Giulia Luise, Filippo Valdettaro, A. Aldo Faisal
2023	J	`jnl`	Bag of Policies for Distributional Deep Exploration. CoRR Asen Nachkov, Luchen Li, Giulia Luise, Filippo Valdettaro, Aldo A. Faisal
2023	A*	`conf`	Meta Optimal Transport. ICML Brandon Amos, Giulia Luise, Samuel Cohen, Ievgen Redko
2023	A*	`conf`	On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology. ICML Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein
2023	J	`jnl`	On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology. CoRR Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio', Michael M. Bronstein
2022	J	`jnl`	Heterogeneous manifolds for curvature-aware graph embedding. CoRR Francesco Di Giovanni, Giulia Luise, Michael M. Bronstein
2022	J	`jnl`	Meta Optimal Transport. CoRR Brandon Amos, Samuel Cohen, Giulia Luise, Ievgen Redko
2022	J	`jnl`	Schedule-Robust Online Continual Learning. CoRR Ruohan Wang, Marco Ciccone, Giulia Luise, Andrew Yapp, Massimiliano Pontil, Carlo Ciliberto
2021	A	`conf`	Aligning Time Series on Incomparable Spaces. AISTATS Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Peter Deisenroth
2021	J	`jnl`	Enabling risk-aware Reinforcement Learning for medical interventions through uncertainty decomposition. CoRR Paul Festor, Giulia Luise, Matthieu Komorowski, A. Aldo Faisal
2021	—	`—`	Entropic optimal transport in machine learning: applications to distributional regression, barycentric estimation and probability matching. Giulia Luise
2020	A*	`conf`	A Non-Asymptotic Analysis for Stein Variational Gradient Descent. NeurIPS Anna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton
2020	J	`jnl`	A Non-Asymptotic Analysis for Stein Variational Gradient Descent. CoRR Anna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton
2020	J	`jnl`	Aligning Time Series on Incomparable Spaces. CoRR Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Peter Deisenroth
2020	A*	`conf`	Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning. NeurIPS Luca Oneto, Michele Donini, Giulia Luise, Carlo Ciliberto, Andreas Maurer, Massimiliano Pontil
2020	J	`jnl`	Generalization Properties of Optimal Transport GANs with Latent Distribution Learning. CoRR Giulia Luise, Massimiliano Pontil, Carlo Ciliberto
2020	A*	`conf`	The Wasserstein Proximal Gradient Algorithm. NeurIPS Adil Salim, Anna Korba, Giulia Luise
2019	A*	`conf`	Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction. ICML Giulia Luise, Dimitrios Stamos, Massimiliano Pontil, Carlo Ciliberto
2019	J	`jnl`	Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction. CoRR Giulia Luise, Dimitris Stamos, Massimiliano Pontil, Carlo Ciliberto
2019	A*	`conf`	Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm. NeurIPS Giulia Luise, Saverio Salzo, Massimiliano Pontil, Carlo Ciliberto
2019	J	`jnl`	Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm. CoRR Giulia Luise, Saverio Salzo, Massimiliano Pontil, Carlo Ciliberto
2018	A*	`conf`	Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance. NeurIPS Giulia Luise, Alessandro Rudi, Massimiliano Pontil, Carlo Ciliberto
2018	J	`jnl`	Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance. CoRR Giulia Luise, Alessandro Rudi, Massimiliano Pontil, Carlo Ciliberto