Rivasplata, Omar

9 publications

ICLR 2025 Generalization and Distributed Learning of GFlowNets Tiago Silva, Amauri H Souza, Omar Rivasplata, Vikas Garg, Samuel Kaski, Diego Mesquita

TMLR 2025 Regularized Gradient Clipping Provably Trains Wide and Deep Neural Networks Matteo Tucat, Anirbit Mukherjee, Mingfei Sun, Procheta Sen, Omar Rivasplata

TMLR 2024 A Note on the Convergence of Denoising Diffusion Probabilistic Models Sokhna Diarra Mbacke, Omar Rivasplata

NeurIPS 2021 On the Role of Optimization in Double Descent: A Least Squares Study Ilja Kuzborskij, Csaba Szepesvari, Omar Rivasplata, Amal Rannen-Triki, Razvan Pascanu

JMLR 2021 Tighter Risk Certificates for Neural Networks María Pérez-Ortiz, Omar Rivasplata, John Shawe-Taylor, Csaba Szepesvári

NeurIPSW 2021 Towards Better Visual Explanations for Deep Image Classifiers Agnieszka Grabska-Barwinska, Amal Rannen-Triki, Omar Rivasplata, András György

NeurIPS 2020 Logarithmic Pruning Is All You Need Laurent Orseau, Marcus Hutter, Omar Rivasplata

NeurIPS 2020 PAC-Bayes Analysis Beyond the Usual Bounds Omar Rivasplata, Ilja Kuzborskij, Csaba Szepesvari, John Shawe-Taylor

NeurIPS 2018 PAC-Bayes Bounds for Stable Algorithms with Instance-Dependent Priors Omar Rivasplata, Emilio Parrado-Hernandez, John S Shawe-Taylor, Shiliang Sun, Csaba Szepesvari