46 citations · 177 across the 41 of their papers we have counts for
7 papers · 1 filter
Unsupervised Learning of Structured Representations via Closed-Loop Transcription
Shengbang Tong, Xili Dai, Yubei Chen +5
This paper proposes an unsupervised method for learning a unified representation that serves both discriminative and generative purposes. While most existing unsupervised learning…
Simple Emergent Action Representations from Multi-Task Policy Training
Pu Hua, Yubei Chen, Huazhe Xu
The low-level sensory and motor signals in deep reinforcement learning, which exist in high-dimensional spaces such as image observations or motor torques, are inherently challengi…
Joint Embedding Self-Supervised Learning in the Kernel Regime
Bobak T. Kiani, Randall Balestriero, Yubei Chen +2
The fundamental goal of self-supervised learning (SSL) is to produce useful representations of data without access to any labels for classifying the data. Modern methods in SSL, wh…
Minimalistic Unsupervised Learning with the Sparse Manifold Transform
Yubei Chen, Zeyu Yun, Yi Ma +2
We describe a minimalistic and interpretable method for unsupervised learning, without resorting to data augmentation, hyperparameter tuning, or other engineering designs, that ach…
Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning
Yubei Chen, Adrien Bardes, Zengyi Li +1
Self-supervised learning (SSL) has recently achieved tremendous empirical advancements in learning image representation. However, our understanding of the principle behind learning…
On the duality between contrastive and non-contrastive self-supervised learning
Quentin Garrido, Yubei Chen, Adrien Bardes +2
Recent approaches in self-supervised learning of image representations can be categorized into different families of methods and, in particular, can be divided into contrastive and…
Neural Manifold Clustering and Embedding
Zengyi Li, Yubei Chen, Yann LeCun +1
Given a union of non-linear manifolds, non-linear subspace clustering or manifold clustering aims to cluster data points based on manifold structures and also learn to parameterize…