Poster "representation learning" Papers
137 papers found • Page 2 of 3
Conference
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.
PaPaGei: Open Foundation Models for Optical Physiological Signals
Arvind Pillai, Dimitris Spathis, Fahim Kawsar et al.
Predictive Coding Enhances Meta-RL To Achieve Interpretable Bayes-Optimal Belief Representation Under Partial Observability
Po-Chen Kuo, Han Hou, Will Dabney 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.
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
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.
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
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.
Wasserstein-Regularized Conformal Prediction under General Distribution Shift
Rui Xu, Chao Chen, Yue Sun et al.
WildSAT: Learning Satellite Image Representations from Wildlife Observations
Rangel Daroya, Elijah Cole, Oisin Mac Aodha et al.
You Are Your Own Best Teacher: Achieving Centralized-level Performance in Federated Learning under Heterogeneous and Long-tailed Data
Shanshan Yan, Zexi Li, Chao Wu et al.
A Global Geometric Analysis of Maximal Coding Rate Reduction
Peng Wang, Huikang Liu, Druv Pai et al.
An Information Theoretical View for Out-Of-Distribution Detection
Jinjing Hu, Wenrui Liu, Hong Chang 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
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.
CLOSER: Towards Better Representation Learning for Few-Shot Class-Incremental Learning
Junghun Oh, Sungyong Baik, Kyoung Mu Lee
Contrastive Learning for Clinical Outcome Prediction with Partial Data Sources
Xia, Jonathan Wilson, Benjamin Goldstein et al.
CricaVPR: Cross-image Correlation-aware Representation Learning for Visual Place Recognition
Feng Lu, Xiangyuan Lan, Lijun Zhang 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