"representation learning" Papers
75 papers found • Page 1 of 2
$\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
Vlad Sobal, Mark Ibrahim, Randall Balestriero et al.
AmorLIP: Efficient Language-Image Pretraining via Amortization
Haotian Sun, Yitong Li, Yuchen Zhuang et al.
A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics
Licong Lin, Song Mei
A Unifying Framework for Representation Learning
Shaden Alshammari, John Hershey, Axel Feldmann et al.
Boosting Multiple Views for pretrained-based Continual Learning
Quyen Tran, Tung Lam Tran, Khanh Doan et al.
Can LLMs Reason Over Non-Text Modalities in a Training-Free Manner? A Case Study with In-Context Representation Learning
Tianle Zhang, Wanlong Fang, Jonathan Woo et al.
Deep Kernel Posterior Learning under Infinite Variance Prior Weights
Jorge Loría, Anindya Bhadra
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
Ivan Butakov, Alexander Semenenko, Alexander Tolmachev et al.
Harnessing Feature Resonance under Arbitrary Target Alignment for Out-of-Distribution Node Detection
Shenzhi Yang, Junbo Zhao, Sharon Li et al.
How Classifier Features Transfer to Downstream: An Asymptotic Analysis in a Two-Layer Model
HEE BIN YOO, Sungyoon Lee, Cheongjae Jang et al.
How Far Are We from True Unlearnability?
Kai Ye, Liangcai Su, Chenxiong Qian
OGBench: Benchmarking Offline Goal-Conditioned RL
Seohong Park, Kevin Frans, Benjamin Eysenbach et al.
OLinear: A Linear Model for Time Series Forecasting in Orthogonally Transformed Domain
Wenzhen Yue, Yong Liu, Hao Wang et al.
On the creation of narrow AI: hierarchy and nonlocality of neural network skills
Eric Michaud, Asher Parker-Sartori, Max Tegmark
On the Feature Learning in Diffusion Models
Andi Han, Wei Huang, Yuan Cao et al.
Rotary Masked Autoencoders are Versatile Learners
Uros Zivanovic, Serafina Di Gioia, Andre Scaffidi et al.
Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
Achleshwar Luthra, Tianbao Yang, Tomer Galanti
Towards Cross-modal Backward-compatible Representation Learning for Vision-Language Models
Young Kyun Jang, Ser-Nam Lim
T-REGS: Minimum Spanning Tree Regularization for Self-Supervised Learning
Julie Mordacq, David Loiseaux, Vicky Kalogeiton et al.
USP: Unified Self-Supervised Pretraining for Image Generation and Understanding
Xiangxiang Chu, Renda Li, Yong Wang
Vision‑Language‑Vision Auto‑Encoder: Scalable Knowledge Distillation from Diffusion Models
Tiezheng Zhang, Yitong Li, Yu-Cheng Chou et al.
Adaptive Discovering and Merging for Incremental Novel Class Discovery
Guangyao Chen, Peixi Peng, Yangru Huang et al.
A Global Geometric Analysis of Maximal Coding Rate Reduction
Peng Wang, Huikang Liu, Druv Pai et al.
An Unsupervised Approach for Periodic Source Detection in Time Series
Berken Utku Demirel, Christian Holz
Autoencoding Conditional Neural Processes for Representation Learning
Victor Prokhorov, Ivan Titov, Siddharth N
BaCon: Boosting Imbalanced Semi-supervised Learning via Balanced Feature-Level Contrastive Learning
Qianhan Feng, Lujing Xie, Shijie Fang et al.
BeigeMaps: Behavioral Eigenmaps for Reinforcement Learning from Images
Sandesh Adhikary, Anqi Li, Byron Boots
Beyond Prototypes: Semantic Anchor Regularization for Better Representation Learning
Yanqi Ge, Qiang Nie, Ye Huang et al.
Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains
Kyungeun Lee, Ye Seul Sim, Hye-Seung Cho et al.
Bridging Mini-Batch and Asymptotic Analysis in Contrastive Learning: From InfoNCE to Kernel-Based Losses
Panagiotis Koromilas, Giorgos Bouritsas, Theodoros Giannakopoulos et al.
CLAP: Isolating Content from Style through Contrastive Learning with Augmented Prompts
Yichao Cai, Yuhang Liu, Zhen Zhang et al.
Contrastive Continual Learning with Importance Sampling and Prototype-Instance Relation Distillation
Jiyong Li, Dilshod Azizov, Yang LI et al.
Contrastive Learning for Clinical Outcome Prediction with Partial Data Sources
Xia, Jonathan Wilson, Benjamin Goldstein et al.
Cross-Domain Policy Adaptation by Capturing Representation Mismatch
Jiafei Lyu, Chenjia Bai, Jing-Wen Yang et al.
Data-to-Model Distillation: Data-Efficient Learning Framework
Ahmad Sajedi, Samir Khaki, Lucy Z. Liu et al.
Deep Regression Representation Learning with Topology
Shihao Zhang, Kenji Kawaguchi, Angela Yao
Differentially Private Representation Learning via Image Captioning
Tom Sander, Yaodong Yu, Maziar Sanjabi et al.
Diffusion Language Models Are Versatile Protein Learners
Xinyou Wang, Zaixiang Zheng, Fei YE et al.
Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification
Jintong Gao, He Zhao, Dandan Guo et al.
Dynamic Data Selection for Efficient SSL via Coarse-to-Fine Refinement
Aditay Tripathi, Pradeep Shenoy, Anirban Chakraborty
DySeT: a Dynamic Masked Self-distillation Approach for Robust Trajectory Prediction
MOZHGAN POURKESHAVARZ, Arielle Zhang, Amir Rasouli
Elucidating the Hierarchical Nature of Behavior with Masked Autoencoders
Lucas Stoffl, Andy Bonnetto, Stéphane D'Ascoli et al.
Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction
Pranav Singh Chib, Pravendra Singh
Exploring Diverse Representations for Open Set Recognition
Yu Wang, Junxian Mu, Pengfei Zhu et al.
Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits
Jiabin Lin, Shana Moothedath, Namrata Vaswani
Feasibility Consistent Representation Learning for Safe Reinforcement Learning
Zhepeng Cen, Yihang Yao, Zuxin Liu et al.
Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to Generalize
Tianren Zhang, Chujie Zhao, Guanyu Chen et al.
FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data
Shusen Jing, Anlan Yu, Shuai Zhang et al.
Graph2Tac: Online Representation Learning of Formal Math Concepts
Lasse Blaauwbroek, Mirek Olšák, Jason Rute et al.
How Learning by Reconstruction Produces Uninformative Features For Perception
Randall Balestriero, Yann LeCun