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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