Matteo Pagliardini | DeepAI

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∙ 06/01/2023

Faster Causal Attention Over Large Sequences Through Sparse Flash Attention

Transformer-based language models have found many diverse applications r...

0 Matteo Pagliardini, et al. ∙

∙ 10/27/2022

Revisiting the ACVI Method for Constrained Variational Inequalities

ACVI is a recently proposed first-order method for solving variational i...

0 Tatjana Chavdarova, et al. ∙

∙ 02/11/2022

Improving Generalization via Uncertainty Driven Perturbations

Recently Shah et al., 2020 pointed out the pitfalls of the simplicity bi...

7 Matteo Pagliardini, et al. ∙

∙ 02/09/2022

Agree to Disagree: Diversity through Disagreement for Better Transferability

Gradient-based learning algorithms have an implicit simplicity bias whic...

0 Matteo Pagliardini, et al. ∙

∙ 12/09/2021

The Peril of Popular Deep Learning Uncertainty Estimation Methods

Uncertainty estimation (UE) techniques – such as the Gaussian process (G...

0 Yehao Liu, et al. ∙

∙ 06/25/2020

Taming GANs with Lookahead

Generative Adversarial Networks are notoriously challenging to train. Th...

12 Tatjana Chavdarova, et al. ∙

∙ 04/10/2019

Better Word Embeddings by Disentangling Contextual n-Gram Information

Pre-trained word vectors are ubiquitous in Natural Language Processing a...

0 Prakhar Gupta, et al. ∙

∙ 03/07/2017

Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Features

The recent tremendous success of unsupervised word embeddings in a multi...

0 Matteo Pagliardini, et al. ∙

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