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03/31/2023
Simple Sorting Criteria Help Find the Causal Order in Additive Noise Models
Additive Noise Models (ANM) encode a popular functional assumption that ...
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01/20/2023
Open-Set Likelihood Maximization for Few-Shot Learning
We tackle the Few-Shot Open-Set Recognition (FSOSR) problem, i.e. classi...
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06/18/2022
Model-Agnostic Few-Shot Open-Set Recognition
We tackle the Few-Shot Open-Set Recognition (FSOSR) problem, i.e. classi...
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05/10/2022
Few-Shot Image Classification Benchmarks are Too Far From Reality: Build Back Better with Semantic Task Sampling
Every day, a new method is published to tackle Few-Shot Image Classifica...
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10/15/2021
StreaMulT: Streaming Multimodal Transformer for Heterogeneous and Arbitrary Long Sequential Data
This paper tackles the problem of processing and combining efficiently a...
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05/25/2021
Bridging Few-Shot Learning and Adaptation: New Challenges of Support-Query Shift
Few-Shot Learning (FSL) algorithms have made substantial progress in lea...
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12/26/2020
Spatial Contrastive Learning for Few-Shot Classification
Existing few-shot classification methods rely to some degree on the cros...
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12/03/2020
Stochastic Adversarial Gradient Embedding for Active Domain Adaptation
Unsupervised Domain Adaptation (UDA) aims to bridge the gap between a so...
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07/16/2020
Autoregressive Unsupervised Image Segmentation
In this work, we propose a new unsupervised image segmentation approach ...
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06/25/2020
Target Consistency for Domain Adaptation: when Robustness meets Transferability
Learning Invariant Representations has been successfully applied for rec...
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06/24/2020
Robust Domain Adaptation: Representations, Weights and Inductive Bias
Unsupervised Domain Adaptation (UDA) has attracted a lot of attention in...
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06/09/2020
An Overview of Deep Semi-Supervised Learning
Deep neural networks demonstrated their ability to provide remarkable pe...
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03/19/2020
Semi-Supervised Semantic Segmentation with Cross-Consistency Training
In this paper, we present a novel cross-consistency based semi-supervise...
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10/27/2018
