"representation learning" Papers
170 papers found • Page 2 of 4
Conference
Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory
Alexander Levine, Peter Stone, Amy Zhang
Learning from Neighbors: Category Extrapolation for Long-Tail Learning
Shizhen Zhao, Xin Wen, Jiahui Liu et al.
Learning View-invariant World Models for Visual Robotic Manipulation
Jing-Cheng Pang, Nan Tang, Kaiyuan Li et al.
Leaving No OOD Instance Behind: Instance-Level OOD Fine-Tuning for Anomaly Segmentation
Yuxuan Zhang, Zhenbo Shi, han ye et al.
Long-Tailed Recognition via Information-Preservable Two-Stage Learning
Fudong Lin, Xu Yuan
Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization
Tan Pan, Kaiyu Guo, Dongli Xu et al.
Mitigating Spurious Features in Contrastive Learning with Spectral Regularization
Naghmeh Ghanooni, Waleed Mustafa, Dennis Wagner et al.
MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments
MATTHIEU CORD, Antonin Vobecky, Oriane Siméoni et al.
Morphing Tokens Draw Strong Masked Image Models
Taekyung Kim, Byeongho Heo, Dongyoon Han
Neural Thermodynamics: Entropic Forces in Deep and Universal Representation Learning
Liu Ziyin, Yizhou Xu, Isaac Chuang
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.
Orthogonal Contrastive Learning for Multi-Representation fMRI Analysis
Tony Yousefnezhad
PaPaGei: Open Foundation Models for Optical Physiological Signals
Arvind Pillai, Dimitris Spathis, Fahim Kawsar et al.
Parallel-Learning of Invariant and Tempo-variant Attributes of Single-Lead Cardiac Signals: PLITA
Adrian Atienza, Jakob E. Bardram, Sadasivan Puthusserypady
Predictive Coding Enhances Meta-RL To Achieve Interpretable Bayes-Optimal Belief Representation Under Partial Observability
Po-Chen Kuo, Han Hou, Will Dabney et al.
Prior-Constrained Association Learning for Fine-Grained Generalized Category Discovery
Menglin Wang, Zhun Zhong, Xiaojin Gong
Processing and acquisition traces in visual encoders: What does CLIP know about your camera?
Ryan Ramos, Vladan Stojnić, Giorgos Kordopatis-Zilos et al.
Provable Meta-Learning with Low-Rank Adaptations
Jacob Block, Sundararajan Srinivasan, Liam Collins et al.
Provable Sample-Efficient Transfer Learning Conditional Diffusion Models via Representation Learning
Ziheng Cheng, Tianyu Xie, Shiyue Zhang et al.
Provably Efficient Multi-Task Meta Bandit Learning via Shared Representations
Jiabin Lin, Shana Moothedath
Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model
Jiarui Jin, Haoyu Wang, Hongyan Li et al.
Regret Analysis of Multi-task Representation Learning for Linear-Quadratic Adaptive Control
Bruce D. Lee, Leonardo F. Toso, Thomas T. Zhang et al.
Rethinking Classifier Re-Training in Long-Tailed Recognition: Label Over-Smooth Can Balance
Siyu Sun, Han Lu, Jiangtong Li et al.
Rethinking Tokenized Graph Transformers for Node Classification
Jinsong Chen, Chenyang Li, Gaichao Li 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
Simple and Efficient Heterogeneous Temporal Graph Neural Network
Yili Wang, Tairan Huang, Changlong He et al.
Structural Entropy Guided Probabilistic Coding
Xiang Huang, Hao Peng, Li Sun et al.
Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning
Samuel Garcin, Trevor McInroe, Pablo Samuel Castro et al.
Switchable Token-Specific Codebook Quantization For Face Image Compression
Yongbo Wang, Haonan Wang, Guodong Mu et al.
Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling
Cristian Rodriguez-Opazo, Ehsan Abbasnejad, Damien Teney et al.
SynFER: Towards Boosting Facial Expression Recognition with Synthetic Data
Xilin He, Cheng Luo, Xiaole Xian et al.
Temporal Distance-aware Transition Augmentation for Offline Model-based Reinforcement Learning
Dongsu Lee, Minhae Kwon
The Complexity of Learning Sparse Superposed Features with Feedback
Akash Kumar
The Indra Representation Hypothesis
Jianglin Lu, Hailing Wang, Kuo Yang et al.
T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data
Hugo Thimonier, José Lucas De Melo Costa, Fabrice Popineau et al.
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.
Understanding Contrastive Learning via Gaussian Mixture Models
Parikshit Bansal, Ali Kavis, Sujay Sanghavi
Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling
Xiao Li, Zekai Zhang, Xiang Li et al.
UniPre3D: Unified Pre-training of 3D Point Cloud Models with Cross-Modal Gaussian Splatting
Ziyi Wang, Yanran Zhang, Jie Zhou et al.
Unlocking Global Optimality in Bilevel Optimization: A Pilot Study
Quan Xiao, Tianyi Chen
Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints
Yuxuan Wu, Ziyu Wang, Bhiksha Raj et al.
Unsupervised Meta-Learning via In-Context Learning
Anna Vettoruzzo, Lorenzo Braccaioli, Joaquin Vanschoren 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.
Visual Instruction Bottleneck Tuning
Changdae Oh, Jiatong Li, Shawn Im et al.