Niculae, Vlad

21 publications

JMLR 2025 Hopfield-Fenchel-Young Networks: A Unified Framework for Associative Memory Retrieval Saul Santos, Vlad Niculae, Daniel McNamee, Andre F.T. Martins
TMLR 2025 Keep Your Distance: Learning Dispersed Embeddings on $\mathbb{S}_{m}$ Evgeniia Tokarchuk, Hua Chang Bakker, Vlad Niculae
TMLR 2025 On the Low-Rank Parametrization of Reward Models for Controlled Language Generation Sergey Troshin, Vlad Niculae, Antske Fokkens
ICMLW 2024 On the Matter of Embeddings Dispersion on Hyperspheres Evgeniia Tokarchuk, Hua Chang Bakker, Vlad Niculae
ICML 2024 Sparse and Structured Hopfield Networks Saul José Rodrigues Dos Santos, Vlad Niculae, Daniel C Mcnamee, Andre Martins
ICLR 2023 DAG Learning on the Permutahedron Valentina Zantedeschi, Luca Franceschi, Jean Kaddour, Matt Kusner, Vlad Niculae
NeurIPSW 2023 Sparse Modern Hopfield Networks Andre Martins, Vlad Niculae, Daniel C McNamee
TMLR 2023 Wrapped $\beta$-Gaussians with Compact Support for Exact Probabilistic Modeling on Manifolds Sergey Troshin, Vlad Niculae
ICLRW 2022 DAG Learning on the Permutahedron Valentina Zantedeschi, Jean Kaddour, Luca Franceschi, Matt Kusner, Vlad Niculae
ICML 2022 Modeling Structure with Undirected Neural Networks Tsvetomila Mihaylova, Vlad Niculae, Andre Martins
ICLR 2022 Sparse Communication via Mixed Distributions António Farinhas, Wilker Aziz, Vlad Niculae, Andre Martins
JMLR 2022 Sparse Continuous Distributions and Fenchel-Young Losses André F. T. Martins, Marcos Treviso, António Farinhas, Pedro M. Q. Aguiar, Mário A. T. Figueiredo, Mathieu Blondel, Vlad Niculae
ICML 2021 Learning Binary Decision Trees by Argmin Differentiation Valentina Zantedeschi, Matt Kusner, Vlad Niculae
NeurIPS 2020 Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity Gonçalo Correia, Vlad Niculae, Wilker Aziz, André Martins
ICML 2020 LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction Vlad Niculae, Andre Martins
JMLR 2020 Learning with Fenchel-Young Losses Mathieu Blondel, André F.T. Martins, Vlad Niculae
NeurIPS 2020 Sparse and Continuous Attention Mechanisms André Martins, António Farinhas, Marcos Treviso, Vlad Niculae, Pedro Aguiar, Mario Figueiredo
AISTATS 2019 Learning Classifiers with Fenchel-Young Losses: Generalized Entropies, Margins, and Algorithms Mathieu Blondel, Andre Martins, Vlad Niculae
ICML 2018 SparseMAP: Differentiable Sparse Structured Inference Vlad Niculae, Andre Martins, Mathieu Blondel, Claire Cardie
NeurIPS 2017 A Regularized Framework for Sparse and Structured Neural Attention Vlad Niculae, Mathieu Blondel
NeurIPS 2017 Multi-Output Polynomial Networks and Factorization Machines Mathieu Blondel, Vlad Niculae, Takuma Otsuka, Naonori Ueda