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06/08/2023
Improving Visual Prompt Tuning for Self-supervised Vision Transformers
Visual Prompt Tuning (VPT) is an effective tuning method for adapting pr...
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06/02/2023
Probabilistic Concept Bottleneck Models
Interpretable models are designed to make decisions in a human-interpret...
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03/14/2023
Sample-efficient Adversarial Imitation Learning
Imitation learning, in which learning is performed by demonstration, has...
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02/17/2023
New Insights for the Stability-Plasticity Dilemma in Online Continual Learning
The aim of continual learning is to learn new tasks continuously (i.e., ...
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10/25/2022
FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural Networks
Personalized federated learning is aimed at allowing numerous clients to...
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06/14/2022
Confidence Score for Source-Free Unsupervised Domain Adaptation
Source-free unsupervised domain adaptation (SFUDA) aims to obtain high p...
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06/09/2021
Stein Latent Optimization for GANs
Generative adversarial networks (GANs) with clustered latent spaces can ...
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08/20/2020
iCaps: An Interpretable Classifier via Disentangled Capsule Networks
We propose an interpretable Capsule Network, iCaps, for image classifica...
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02/28/2019
PixelSteganalysis: Pixel-wise Hidden Information Removal with Low Visual Degradation
It is difficult to detect and remove secret images that are hidden in na...
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02/26/2019
HexaGAN: Generative Adversarial Nets for Real World Classification
Most deep learning classification studies assume clean data. However, di...
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01/31/2019
AnomiGAN: Generative adversarial networks for anonymizing private medical data
Typical personal medical data contains sensitive information about indiv...
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01/30/2019
PixelSteganalysis: Destroying Hidden Information with a Low Degree of Visual Degradation
Steganography is the science of unnoticeably concealing a secret message...
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07/31/2018
