Self-supervised learning through the eyes of a child
Within months of birth, children develop meaningful expectations about the world around
them. How much of this early knowledge can be explained through generic learning …
them. How much of this early knowledge can be explained through generic learning …
Curriculum learning with infant egocentric videos
S Sheybani, H Hansaria, J Wood… - Advances in Neural …, 2024 - proceedings.neurips.cc
Infants possess a remarkable ability to rapidly learn and process visual inputs. As an infant's
mobility increases, so does the variety and dynamics of their visual inputs. Is this change in …
mobility increases, so does the variety and dynamics of their visual inputs. Is this change in …
Learning high-level visual representations from a child's perspective without strong inductive biases
Young children develop sophisticated internal models of the world based on their visual
experience. Can such models be learned from a child's visual experience without strong …
experience. Can such models be learned from a child's visual experience without strong …
Mine your own view: Self-supervised learning through across-sample prediction
State-of-the-art methods for self-supervised learning (SSL) build representations by
maximizing the similarity between different transformed" views" of a sample. Without …
maximizing the similarity between different transformed" views" of a sample. Without …
Early visual concept learning with unsupervised deep learning
Automated discovery of early visual concepts from raw image data is a major open
challenge in AI research. Addressing this problem, we propose an unsupervised approach …
challenge in AI research. Addressing this problem, we propose an unsupervised approach …
[HTML][HTML] A developmental approach to machine learning?
Visual learning depends on both the algorithms and the training material. This essay
considers the natural statistics of infant-and toddler-egocentric vision. These natural training …
considers the natural statistics of infant-and toddler-egocentric vision. These natural training …
On the surprising similarities between supervised and self-supervised models
How do humans learn to acquire a powerful, flexible and robust representation of objects?
While much of this process remains unknown, it is clear that humans do not require millions …
While much of this process remains unknown, it is clear that humans do not require millions …
Lessons from infant learning for unsupervised machine learning
The desire to reduce the dependence on curated, labeled datasets and to leverage the vast
quantities of unlabeled data has triggered renewed interest in unsupervised (or self …
quantities of unlabeled data has triggered renewed interest in unsupervised (or self …
Self-supervised learning for videos: A survey
The remarkable success of deep learning in various domains relies on the availability of
large-scale annotated datasets. However, obtaining annotations is expensive and requires …
large-scale annotated datasets. However, obtaining annotations is expensive and requires …
Leverage your local and global representations: A new self-supervised learning strategy
Self-supervised learning (SSL) methods aim to learn view-invariant representations by
maximizing the similarity between the features extracted from different crops of the same …
maximizing the similarity between the features extracted from different crops of the same …