ICLR "self-supervised learning" Papers
21 papers found
$\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
Vlad Sobal, Mark Ibrahim, Randall Balestriero et al.
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
Yu Huang, Zixin Wen, Yuejie Chi et al.
BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacoustics
Lukas Rauch, Raphael Schwinger, Moritz Wirth et al.
Boost Self-Supervised Dataset Distillation via Parameterization, Predefined Augmentation, and Approximation
Sheng-Feng Yu, Jia-Jiun Yao, Wei-Chen Chiu
Can a MISL Fly? Analysis and Ingredients for Mutual Information Skill Learning
Chongyi Zheng, Jens Tuyls, Joanne Peng et al.
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
Ivan Butakov, Alexander Semenenko, Alexander Tolmachev et al.
Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass
Tong Chen, Hao Fang, Patrick Xia et al.
HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adapters
YUJIE MO, Runpeng Yu, Xiaofeng Zhu et al.
Learning Mask Invariant Mutual Information for Masked Image Modeling
Tao Huang, Yanxiang Ma, Shan You et al.
MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer
Yuancheng Wang, Haoyue Zhan, Liwei Liu et al.
Navigation-Guided Sparse Scene Representation for End-to-End Autonomous Driving
Peidong Li, Dixiao Cui
PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis
Satoki Ishikawa, Makoto Yamada, Han Bao et al.
Physics-informed Temporal Difference Metric Learning for Robot Motion Planning
Ruiqi Ni, zherong pan, Ahmed Hussain Qureshi
Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning
Ruikun Li, Huandong Wang, Qingmin Liao et al.
Self-Supervised Diffusion Models for Electron-Aware Molecular Representation Learning
Gyoung S. Na, Chanyoung Park
Self-Supervised Diffusion MRI Denoising via Iterative and Stable Refinement
Chenxu Wu, Qingpeng Kong, Zihang Jiang et al.
STORM: Spatio-TempOral Reconstruction Model For Large-Scale Outdoor Scenes
Jiawei Yang, Jiahui Huang, Boris Ivanovic et al.
SyllableLM: Learning Coarse Semantic Units for Speech Language Models
Alan Baade, Puyuan Peng, David Harwath
Towards Self-Supervised Covariance Estimation in Deep Heteroscedastic Regression
Megh Shukla, Aziz Shameem, Mathieu Salzmann et al.
UNSURE: self-supervised learning with Unknown Noise level and Stein's Unbiased Risk Estimate
Julián Tachella, Mike Davies, Laurent Jacques
Video In-context Learning: Autoregressive Transformers are Zero-Shot Video Imitators
Wentao Zhang, Junliang Guo, Tianyu He et al.