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Unsupervised Learning

Group Robust Classification Without Any Group Information
Group Robust Classification Without Any Group Information
Empirical risk minimization (ERM) is sensitive to spurious correlations present in training data, which poses a significant risk when …
Conference on Neural Information Processing Systems (NeurIPS),  2023.
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Choreographer: Learning and Adapting Skills in Imagination
Choreographer: Learning and Adapting Skills in Imagination
Unsupervised skill learning aims to learn a rich repertoire of behaviors without external supervision, providing artificial agents with …
International Conference of Learning Representations (ICLR),  2023.
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Choreographer: Learning and Adapting Skills in Imagination
Choreographer: Learning and Adapting Skills in Imagination
Unsupervised skill learning aims to learn a rich repertoire of behaviors without external supervision, providing artificial agents with …
Workshop at the Neural Information Processing Systems (NeurIPS),  2022.
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Overcoming challenges in leveraging GANs for few-shot data augmentation
Overcoming challenges in leveraging GANs for few-shot data augmentation
In this paper, we explore the use of GAN-based few-shot data augmentation as a method to improve few-shot classification performance. …
Workshop at the Conference on Lifelong Learning Agents (CoLLAs),  2022.
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Unsupervised Model-based Pre-training for Data-efficient Reinforcement Learning from Pixels
Unsupervised Model-based Pre-training for Data-efficient Reinforcement Learning from Pixels
Reinforcement learning (RL) aims at autonomously performing complex tasks. To this end, a reward signal is used to steer the learning …
Workshop at the International Conference on Machine Learning (ICML),  2022.
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Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
Remote sensing and automatic earth monitoring are key to solve global-scale challenges such as disaster prevention, land use …
International Conference on Computer Vision (ICCV),  2021.
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Unsupervised Learning of Dense Visual Representations
Unsupervised Learning of Dense Visual Representations
Contrastive self-supervised learning has emerged as a promising approach to unsupervised visual representation learning. In general, …
Conference on Neural Information Processing Systems (NeurIPS),  2020.
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A Closer Look at the Optimization Landscapes of Generative Adversarial Networks
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks
Generative adversarial networks have been very successful in generative modeling, however they remain relatively challenging to train …
International Conference on Learning Representations (ICLR),  2020.
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Neocortical plasticity: an unsupervised cake but no free lunch
Neocortical plasticity: an unsupervised cake but no free lunch
The fields of artificial intelligence and neuroscience have a long history of fertile bi-directional interactions. On the one hand, …
Workshop at the Neural Information Processing Systems (NeurIPS),  2019.
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On Adversarial Mixup Resynthesis
On Adversarial Mixup Resynthesis
In this paper, we explore new approaches to combining information encoded within the learned representations of auto-encoders. We …
Conference on Neural Information Processing Systems (NeurIPS),  2019.
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