510 citations · 972 across the 24 of their papers we have counts for
5 papers · 1 filter
A soft nearest-neighbor framework for continual semi-supervised learning
Zhiqi Kang, Enrico Fini, Moin Nabi +2
Despite significant advances, the performance of state-of-the-art continual learning approaches hinges on the unrealistic scenario of fully labeled data. In this paper, we tackle t…
miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings
Tassilo Klein, Moin Nabi
This paper presents miCSE, a mutual information-based contrastive learning framework that significantly advances the state-of-the-art in few-shot sentence embedding. The proposed a…
Mixture-of-experts VAEs can disregard variation in surjective multimodal data
Jannik Wolff, Tassilo Klein, Moin Nabi +2
Machine learning systems are often deployed in domains that entail data from multiple modalities, for example, phenotypic and genotypic characteristics describe patients in healthc…
SCD: Self-Contrastive Decorrelation for Sentence Embeddings
Tassilo Klein, Moin Nabi
In this paper, we propose Self-Contrastive Decorrelation (SCD), a self-supervised approach. Given an input sentence, it optimizes a joint self-contrastive and decorrelation objecti…
Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation
Guanglei Yang, Enrico Fini, Dan Xu +5
A fundamental and challenging problem in deep learning is catastrophic forgetting, i.e. the tendency of neural networks to fail to preserve the knowledge acquired from old tasks wh…